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Models Quantify the Relationship Between Water Flows/Levels and
Ecological Endpoints
National Conference on Ecosystem Restoration
Los Angeles, CA
July 20-24, 2009
Joseph V. DePinto, Todd M. Redder,
Scott Bell, Laura Weintraub
LimnoTech (www.Limno.com)
Ann Arbor, MI
Presentation Outline
� Background: two initiatives that recognize importance of hydrology/hydraulics to ecosystem structure and function
� ESWM framework of The Nature Conservancy
� Great Lakes Water Compact� Great Lakes Water Compact
� Previous Flow/Level – Ecological Response Modeling
� Lake Ontario – St. Lawrence River Regulation Evaluation (IERM)
� Muskegon River Watershed linked flow – ecological response modeling (GLECO)
� Conceptual Approach for Sacramento – San Joaquin Bay Delta System
Ecological Sustainable Water Management - The Nature Conservancy (from Richter, et al., 2003)
� Goal: Meet human needs for water by storing and diverting water in a manner that sustains ecological sustains ecological integrity of aquatic ecosystems
� Signed by all Great Lakes States
� Separate Agreement with Canada (Ontario, Quebec)
� Goal: Protect, conserve, restore, improve and effectively manage the Waters and Water
Great Lakes Water Compact
effectively manage the Waters and Water Dependent Natural Resources of the Basin
� Specifically: prevent significant adverse impacts of water Withdrawals and Losses on the Basin's ecosystems and watersheds
Moses Saunders Dam
(Plan 1958DD)
Lower St.
Lawrence River
Quebec
Trois-Rivieres
Lake Ontario – St. Lawrence River Water Level/Flow Regulation Study
Goal: Evaluate existing regulation plan and recommend alternative plan that best satisfies the needs of multiple interests: environment, riparian landowners, hydropower, commercial navigation, recreational boating, water supplies)
Lake OntarioUpper St.
Lawrence River
Toronto
Montreal
Rochester
Canada
U.S.
Trois-Rivieres
Integrated Ecological Response Model (IERM)
� Designed to compare response of Ecological Performance Indicators (PI’s) to alternative Hydrologic/Hydraulic (H&H) conditions� Compare alternative Regulation Plans under a given Basin Supply Scenario
�� Other stressors assumed constant for comparisonOther stressors assumed constant for comparison
� Composed of sub-models for each PI group� PI response algorithms only as complex as data will allow� PI response algorithms only as complex as data will allow� Range of complexity from simple empirical relationships (PI vs water level function) to more complex process-oriented population sub-models
� Work with researchers to integrate the science� Build Conceptual model: understand data availability & connections between various studies (2002-04)
� Identify specific performance indicators and associated metrics
� Evaluate and interpret the model
Reduce Analysis to 32 “Key” PIs
Lake Ontario /
Upper St. Lawrence
Key PIs (19)
SAR (4)
Mammal (1)
Herptiles (0)
Fish (11)
Vegetation
(1)
Lower St. Lawrence
Key PIs (13)
Birds (2)Fish (11)
Vegetation
(0)Fish (3)
Birds (4)
Herptiles (1)
Mammal (1)
SAR (4)
Key PIs based on:• Representativeness/significance
• Certainty
• Sensitivity to regulation
• Geographic coverage
IERM Conceptual Model (Lake Ontario)
Wetland Habitat
Lake Ontario
Water Level
•Weekly WL time series
Water Temperature
•Nearshore temperature
•Wetland temperatureWetland Birds
•Frequency of low-
water years
•Frequency of high-
water years
• Nest access
•Nest flooding
• Wetland access
•Stranding potential
•Weighted
usable area
Wetland Habitat
Lake Ontario
Water Level
•Weekly WL time series
Water Temperature
•Nearshore temperature
•Wetland temperatureWetland Birds
•Frequency of low-
water years
•Frequency of high-
water years
• Nest access
•Nest flooding
• Wetland access
•Stranding potential
•Weighted
usable area
•Meadow marsh area
•Cattail area
•Floating leaf area
•Suitable habitat area
(acres)
• Nesting success
Fish (multiple species)
•Year-class strength (no./yr)
•Biomass (kg/ha)
•Production (no./ha/yr)
Muskrats
• Muskrat houses per acre
•Cattail usage
•Timing of
spawning events
•Habitat loss due to
flooding/stranding
•Weighted usable
area for various life
stages
Endangered Species
•Suitable habitat area
Amphibians/Reptiles
•Suitable habitat area
•WL fluctuations
•Flood
magnitude/duration
•Weighted
usable area
•Weighted
usable area
•Meadow marsh area
•Cattail area
•Floating leaf area
•Suitable habitat area
(acres)
• Nesting success
Fish (multiple species)
•Year-class strength (no./yr)
•Biomass (kg/ha)
•Production (no./ha/yr)
Muskrats
• Muskrat houses per acre
•Cattail usage
•Timing of
spawning events
•Habitat loss due to
flooding/stranding
•Weighted usable
area for various life
stages
Endangered Species
•Suitable habitat area
Amphibians/Reptiles
•Suitable habitat area
•WL fluctuations
•Flood
magnitude/duration
•Weighted
usable area
•Weighted
usable area
Wetland Plant Sub-Model (LO/USL)
LO/USL Water Level Time
Series
•Flooding – elevations
inundated for 4 consecutive
QM during growing season
•Dewatering – elevations dry
during entire growing season
% Species Composition @
Specific Elevations
•Barrier Beach
•Drowned River Mouth
•Protected Embayment
•Unprotected Embayment
Mo
del
In
pu
ts Su
b-M
od
el Ou
tpu
ts
Feed to Faunal
Sub-Models
Wetland Plant
PI Measures
“Typical” Wetland
Topography
•Barrier Beach
•Drowned River Mouth
•Protected Embayment
•Unprotected Embayment
Total Estimated Area of
Plant Species (ha)
•Barrier Beach
•Drowned River Mouth
•Protected Embayment
•Unprotected EmbaymentLO/USL Wetland Area
•Barrier Beach
•Drowned River Mouth
•Protected Embayment
•Unprotected Embayment
•Unprotected Embayment
Su
b-M
od
el I
np
uts
Mo
del O
utp
uts
Feed to Faunal
Sub-Models
Wetland Plant
Effects
IERM “PI Time Series” Diagram
IERM “Target” Diagram
IERM Plan Evaluation Results (Lake Ontario / Upper River – 19 PIs)
10
15
20
Net # o
f P
Is w
/ S
ignific
ant G
ain
s
Historical (1900-2000)
Stochastic #1 - Wettest Century
Stochastic #2 - Driest Century
Stochastic #3 - Like Historical
Stochastic #4 - Longest Drought
-10
-5
0
5
Plan A
Net # o
f P
Is w
/ S
ignific
ant G
ain
s
Plan A Plan D Plan B PreProject
IERM Plan Evaluation Results (Entire LOSL System – 32 PIs)
10
15
20
Net # o
f P
Is w
/ S
ignific
ant G
ain
s
Historical (1900-2000)
Stochastic #1 - Wettest Century
Stochastic #2 - Driest Century
Stochastic #3 - Like Historical
Stochastic #4 - Longest Drought
-10
-5
0
5
Plan A
Net # o
f P
Is w
/ S
ignific
ant G
ain
s
Plan A Plan D Plan B PreProject
Channel
Modifications
Natural Hydrological &
Climatological Forcings
Other Management Actions
& System Stressors
River Channel Flow
Regime
Drainage Basin
Properties
Water
Use
Watershed
Runoff Quantity
Watershed
Runoff Quality
•Nutrient loads
•Solids loads
Groundwater
Flow Regime
Str
esso
rsF
low
R
esponse
Addressing Great Lakes Withdrawal IssuesGreat Lakes Watershed Ecosystem Model (GLECO)
Ass
essm
ent
Ind
icat
ors Riparian Wetland
Vegetation
•Plant diversity
Water Quality•Nutrients
•Solids
River Hydraulics
•Flow/Volume•Depth
•Velocity
Temperature
Fish Habitat
•Weighted usable
habitat area
Fish Population
GLECO development and application to Muskegon Watershed (MI)
� Configure Hydrologic Simulation Program – FORTRAN (HSPF) to watershed based on geomorphic, hydrologic, land use/cover data
� Link HSPF to required ecological sub-models
� Calibrate flow and water quality parameters at various sampling locations� Establish baseline condition for relevant ecological endpoints.� Establish baseline condition for relevant ecological endpoints.
� Run model forecasts of withdrawal scenarios & compare to baseline
Model Scenario Application: Little Muskegon River
� Scenario “A”
� Single withdrawal
� Withdrawal of 5 MGD from the Little Muskegon River
catchment #1
� Scenario “B”:
Cumulative withdrawal� Cumulative withdrawal
� Withdrawal of 5 MGD from the Little Muskegon River
catchment #1 & catchment #2 (10 mgd total)
� Withdrawals modify channel hydraulics and water
temperature
� Withdrawals reduce suitable spawning habitat area
for brown trout by 20-50%
0.0
0.2
0.4
0.6
0.8
1.0
Hab
itat
Su
itab
ilit
y In
dex (
HS
I)
Brown Trout: Spawning Habitat Suitability Functions
� Brown trout spawning
habitat is impacted by
water temperature, depth,
and stream velocity.
� Based on U.S. Fish &
Wildlife Service brown trout 0.0
0 10 20 30 40 50 60 70 80
Water Temperature (deg. F)
Hab
itat
Su
itab
ilit
y In
dex (
HS
I)
Wildlife Service brown trout
habitat report (1986).
0.0
0.2
0.4
0.6
0.8
1.0
0.0 0.5 1.0 1.5 2.0
Stream Depth (feet)
Hab
itat
Su
itab
ilit
y In
dex (
HS
I)
0.0
0.2
0.4
0.6
0.8
1.0
0.0 1.0 2.0 3.0 4.0
Stream Velocity (ft/sec)
Hab
itat
Su
itab
ilit
y In
dex (
HS
I)
Withdrawal Scenarios for Little Muskegon River sub-basin
� Model generates geographic comparisons of withdrawal
scenarios (red, green) relative to baseline (blue) for
spawning habitat (average annual weighted suitable area):
GW: 5 mgdMuskegon
GW: 5 mgd
GW: 5 mgd
GW: 5 mgd
Little Muskegon River
Muskegon
River
Comparison of Habitat Results
� Model generates temporal comparisons of
scenario simulation results relative to
baseline:
� The Bay Delta system is managed both in terms of water quantity and water quality.
� There are multiple stakeholders with varying priorities
� Reclamation and other management and project decisions must consider ecological impacts
Sacramento – San Joaquin Bay Delta Integrated Ecological Response Model: Concepts
Reclamation Project
20
Reclamation Project Dam
Canal
New flow mgmt. plan
Modification of System Conditions
Flow volume
Velocity
Temperature
Salinity
Ecosystem Receptor
Fish
Waterfowl
Wetland habitat
Bay Delta Integrated Ecological Response Model: Challenges
� Must provide for protection and recovery of endangered and sensitive species, as well as protection and restoration of water supplies
� Multiple projects to consider, each may affect multiple environmental driversmultiple environmental drivers
� Multiple ecological receptors: delta smelt, Chinook salmon, green sturgeon, riparian wetlands, migratory waterfowl, etc.
� Cumulative impacts may exist
� Must overlay management on natural hydrometeorological conditions (climate change?)
21
DSM2-SJR Model
Hydraulic Sub-Model (HYDRO)
•Predicted flow @
Vernalis
Water Quality Sub-Model (QUAL)
•Predicted salinity in
delta area
Math
em
ati
cal M
od
els
SJR System OperationsTributary boundary inflows,
diversions, return flows
Hydrology
Sys
tem
S
tre
ss
ors
Vernalis delta area
Delta Smelt
•Population indices:
1) SJR-Sacramento
confluence
2) Suisun Bay
Chinook Salmon
•Smolt out-migration
(mean flow in spring)
•Adult escapement
(mean flow in fall)
Ecological Response Sub-Models
Predicted flow @
Vernalis
Predicted salinity
in delta area
Math
em
ati
cal M
od
els
22
Model Scenario Application: Little Muskegon River
Little Muskegon
River Watershed