watershed/nutrients/physical forcing
DESCRIPTION
Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystems. Watershed/nutrients/physical forcing. TEAM:. Dimitry Beletsky, Tom Croley, Carlo De Marchi, Joe Depinto, Juli Dyble, Gary Fahnenstiel Tom Johengen, - PowerPoint PPT PresentationTRANSCRIPT
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Watershed/nutrients/physical forcing
Adaptive Integrated Framework (AIF): a new methodology for Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystemsmanaging impacts of multiple stressors in coastal ecosystems
TEAM: Dimitry Beletsky, Dimitry Beletsky, Tom Croley, Tom Croley,
Carlo De Marchi, Carlo De Marchi, Joe Depinto, Joe Depinto, Juli Dyble, Juli Dyble,
Gary Fahnenstiel Gary Fahnenstiel Tom Johengen, Tom Johengen,
Donna Kashian andDonna Kashian andCraig StowCraig Stow
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Adaptive Integrated Framework (AIF): a new methodology for Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystemsmanaging impacts of multiple stressors in coastal ecosystems
• Experimental • Monitoring • Synthesis
Water quality
Human health
Coupled biophysical 3D models
Empirically based
(Bayesian)
Artificial neural network
Ecosystem Stressors
Eco
syst
em
Mo
del
s
Fish
community
dynamics
&
Eco
syst
em
end
po
ints
• Land & Resource use
• Climate Change
• Invasive Species
Recommendations for ecosystem characterization
• Economic models• Public preference • Workshops
Socio-economic integration to guide
management
(e.g. regression)
Simple statistical
Ecosystem Characterization • Watershed model• Hydrodynamic model• Biophysical data & processes
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OutlineWatershed/nutrients/physical forcing
- Historical sampling sites and dates
Ecosystem Characterization Ecosystem Characterization • Biophysical data and processes
- Water quality parameters
• Watershed model
• Hydrodynamic model
- Watershed databases
Watershed Nutrient Loading- In Progress
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1991-1996 Saginaw Bay: Study Sites1991-1996 Saginaw Bay: Study Sites
13 sites (8 inner, 5 outer)
sampled by EPA & others(Smith et al. 1977)(Bierman et al. 1984)
1991-1996
1974 - 1980
26 sites (18 inner, 8 outer)
1991-1992
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GLERL Saginaw Bay Monitoring Study 1991 - 1996: Sampling Dates
Year-Cruise Dates Year-Cruise Dates91-1 April 11-18 94-1 April 2091-2 May 1-3 94-2 June 6-1091-3 May 20-21 94-3 July 11-1391-4 June 15-18 94-4 Aug 8-1091-5 July 22-26 94-5 Sept 8-991-6 Aug 19-23 94-6 Oct 17-1991-7 Sept 9-1291-8 Oct 7-2291-9 Nov 8-12
92-1 April 14-15 95-1 May 2-392-2 May 4-6 95-2 May 17-1892-3 May 27 - Jun 3 95-3 June 12-1392-4 June 15-23 95-4 July 17 & 1992-5 July 20-23 95-5 Aug 21-2292-6 Aug 10-12 95-6 Sept 1292-7 Sept 9-15 95-7 Oct 25 & 3092-8 Oct 4-7
93-1 April 29-30 96-1 May 4 & 793-2 May 17 96-2 May 28 & 3093-3 June 21 96-3 June 11-1293-4 July 12 96-4 June 2793-5 Aug 10 96-5 July 15 & 1793-6 Sept 8 96-6 August 2193-7 Oct 5 &14 96-7 September 20
- Between 6 – 9 cruises/yr
- Roughly monthly Apr – Oct
- 2-3 days to sample
Three pilot surveys in 1990(may give best baseline data)
GLERL Saginaw Bay Monitoring Study 1991 - 1996: Sampling Dates
Year-Cruise Dates Year-Cruise Dates91-1 April 11-18 94-1 April 2091-2 May 1-3 94-2 June 6-1091-3 May 20-21 94-3 July 11-1391-4 June 15-18 94-4 Aug 8-1091-5 July 22-26 94-5 Sept 8-991-6 Aug 19-23 94-6 Oct 17-1991-7 Sept 9-1291-8 Oct 7-2291-9 Nov 8-12
92-1 April 14-15 95-1 May 2-392-2 May 4-6 95-2 May 17-1892-3 May 27 - Jun 3 95-3 June 12-1392-4 June 15-23 95-4 July 17 & 1992-5 July 20-23 95-5 Aug 21-2292-6 Aug 10-12 95-6 Sept 1292-7 Sept 9-15 95-7 Oct 25 & 3092-8 Oct 4-7
93-1 April 29-30 96-1 May 4 & 793-2 May 17 96-2 May 28 & 3093-3 June 21 96-3 June 11-1293-4 July 12 96-4 June 2793-5 Aug 10 96-5 July 15 & 1793-6 Sept 8 96-6 August 2193-7 Oct 5 &14 96-7 September 20
LOGISTICS
1991-1996 Saginaw Bay: Sampling Dates1991-1996 Saginaw Bay: Sampling Dates
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1991-1996 Saginaw Bay: Parameters Monitored1991-1996 Saginaw Bay: Parameters Monitored
• Physical/Chemical: CTD profile (w/ Fluorometer and Transmissometer), pH, Alkalinity, Kpar, Secchi, TSS
• Biological: zooplankton, benthos, phytoplankton, chlorophyll, primary production, benthic algae and benthic primary production.
• Nutrients: TP, TDP, SRP, NO3, NH4, SiO2, PSiO2, Cl, DOC, POC
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All water qualitly monitoring data available through two NOAA-GLERL Technical Memos:
•TM-91, Nalepa et al. 1996 includes data for 1991-1993
•TM-115, Johengen et al. 2000 includes data for 1994 – 1996
1991-1996 Saginaw Bay: Data Availability1991-1996 Saginaw Bay: Data Availability
Journal of Great Lakes Research: special volume v21 (1995) Bierman et al. (1984) summarizes data from 1974-1980. Data has been extracted from STORET and in our databases
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OutlineWatershed/nutrients/physical forcing
- Historical sampling sites and dates
Ecosystem Characterization Ecosystem Characterization
• Watershed model
• Hydrodynamic model
• Biophysical data and processes
- Watershed databases
- Water quality parameters
Watershed Nutrient Loading- In Progress
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• Soil (STATSGO)• DEM• 1992 and 2001 Land use • Hydrography • RUSLE 2 Input parameters • DLBRM Hydrologic input parameters • Nutrient (N & P) loading potential
at county & zip code levels• Atrazine loading potential at county
level • Locations of CSOs and SSOs • Water Quality Databases from USGS
and EPA . • Point Sources (Factories & MWWTP)
Available Databases for the Saginaw Bay Watersheds
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AnnualManure
1987, 1992, 1997, 2002N, P205, K20
Fertilizer1987, 1992, 1997, 2002N, P205, K20
Atrazine80% of all pesticide used in Michigan2000, 2001, 2002, 2003, 2004
MonthlyRUSLE2 parameterstopographical factor (slope * slope length)cover factorsupport practice factorsoil erodibility factor 2002
Nitrogen (Manure) Loading
Saginaw Bay Watersheds SurveysSaginaw Bay Watersheds Surveys
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OutlineWatershed/nutrients/physical forcing
- Historical sampling sites and dates
Ecosystem Characterization Ecosystem Characterization
• Watershed model
• Hydrodynamic model
• Biophysical data and processes
- Watershed databases
- Water quality parameters
Watershed Nutrient Loading- In Progress
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The Distributed Large Basin Runoff Model (DLBRM)
• The watershed is subdivided into a grid of square pixels (1 km x 1 km).
• Water and pollutants move horizontally according to the difference in elevation between neighboring pixels
Elevation Flow network
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DLBRM Pixel Water BalanceDLBRM Pixel Water Balance
• Physically based
• Cascade of storage “tanks” (linear reservoirs)
• Degree-day snowmelt
• Three soil layers (U, L, G) plus surface
water (S) and snow pack
• Variable area infiltration
• Potential and actual evapotranspiration
• Lateral transport from upstream pixels
• Model parameters depend on soil characteristics (permeability, etc.)
and land use
s
U
L
G
S
buepU
blepL
aiL
agG
asS
apU
adL
h
bgepG
bsepS
u
l
auU
alL
(s+u)UC
awG
g
InsolationPrecipitationTemperature
Snow Rain
Melt, m
Supply, s
Snow Pack, P
Upper Soil ZoneMoisture, U
Lower Soil ZoneMoisture, L
Groundwater ZoneMoisture, G
Surface Storage,S
Runoff
SurfaceRunoffs UC( )
Evapotranspirationb e Uu p( )
Capacity, C
Evapotranspirationb e Ll p( )
Evapotranspiration
Evaporation
Interflow( )a Li
GroundWater( )a Gg
Basin Outflow( )a Ss
Percolation( )a Up
DeepPercolation
( )a Ldb e Gg p(
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Daily Model Calibrations
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Spatial Characterization of Saginaw Bay Spatial Characterization of Saginaw Bay WatershedsWatersheds
(Augres-Rifle, Kawkawlin-Pine, Saginaw, Pigeon-Wiscoggin)
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Calibrated Saginaw Bay Watershed Calibrated Saginaw Bay Watershed DLBRMDLBRM
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Saginaw River (2003-2006)Saginaw River (2003-2006)
Bias Correlation Nash-Sutcl. RMSE/ Avg. Calib. 50-64 1.048 0.79 0.60 0.79 Calib. 99-02 1.051 0.76 0.19 0.74 Calib. 99-06 1.03 0.82 0.38 0.66
-18
-15
-12
-9
-6
-3
0
3
6
01/01/06 02/20/06 04/11/06 05/31/06 07/20/06 09/08/06 10/28/06 12/17/06
Bas
in n
et s
uppl
y (c
m/d
)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Bas
in o
uflo
w (
cm/d
)
Net Supply Observed 1950-64 1999-02 1999-06
-18
-15
-12
-9
-6
-3
0
3
6
01/01/06 02/20/06 04/11/06 05/31/06 07/20/06 09/08/06 10/28/06 12/17/06
Bas
in n
et s
uppl
y (c
m/d
)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Bas
in o
uflo
w (
cm/d
)
Net Supply Observed 1950-64 1999-02 1999-06
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0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350
Observed Load (g/s)
Estim
ate
d L
oad (
g/s
)
R=0.84
Total Phosphorous Loads for Saginaw River (1989-2005)Total Phosphorous Loads for Saginaw River (1989-2005)
Have: CSO/SSO Fraction of TP Annual Load to Saginaw Bay
• MDEQ• Model predictions
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Calibration of the DLBRM Water Quality Simulations
Available databases• EPA STORET (www.epa.gov/STORET):
The Legacy Data Center contains information prior to 1999 and • The Modernized STORET contains information since 1999. • Permit Compliance System (PCS)- EPA, CSO and SSO – Michigan• EPA NPDES Management System (NMS)- Michigan Department of
Environmental Quality• USGS Water Quality Data (http://waterdata.usgs.gov/nwis)
Problems: • Sporadic sampling, • Poor temporal and spatial coverage, • Uncertain data quality, • Scarcity of water quality parameters
(Suspended sediment concentrations; BOD; E-coli; Total Kjeldahl Nitrogen; Total & Dissolved P, Atrazine)
• Uneasy to manipulate data (ASCII and HTML format)
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OutlineWatershed/nutrients/physical forcing
- Historical sampling sites and dates
Ecosystem Characterization Ecosystem Characterization
• Watershed model
• Hydrodynamic model
• Biophysical data and processes
- Watershed databases
- Water quality parameters
Watershed Nutrient Loading- In Progress
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Hydrodynamic models
• 3D circulation model (POM) Lake-wide 2 km grid, 20-40 vertical levels Output: 3-D circulation, water
temperature, bottom shear stress
• 2D wave model (Schwab et al 1984)
Output: wave-induced bottom shear stress (to calculate resuspension potential)
• 3D particle transport model (Beletsky et al. 2006)
Output: particle trajectories, residence time
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Input data: NWS land and NDBC buoy meteorological observations
Hydrodynamic model
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Model years:
• 1 Historic year (from 1991-1993),
when current observations in Saginaw Bay are available
• 3 Field years (2008,2009, and 2010)
Hydrodynamic modelHydrodynamic model
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OutlineWatershed/nutrients/physical forcing
- Historical sampling sites and dates
Ecosystem Characterization Ecosystem Characterization
• Watershed model
• Hydrodynamic model
• Biophysical data and processes
- Watershed databases
- Water quality parameters
Watershed Nutrient Loading- In Progress
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Watershed Nutrient LoadingIN PROGRESS
ObjectivesObjectives
- provide accurate annual loading of TP, SRP, TN, NO3, TSS for Saginaw River
- sample upstream of Saginaw and downstream Bay City to isolate these 2 major urban sources
- Help parameterize sediment and nutrient transport in DLBRM - event based runoff, high temporal intensity - focus on confluence of 4 main tributaries:
Cass, Flint, Tittabawasse and Shiawassee - 3-4 events in first couple of years
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USGS and MDEQ Water Quality and Discharge Sampling Sites
DEQ samples 12 times a year: Low for model calibrationMultiple Stressor Plan: 30-40 times (incorporate DEQ sites)
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DEQ Contacts1. Christine Aiello
- compiles water quality reports2. Jeff Cooper
- runs biological monitoring component- helping define ‘intensive’ nutrient source study, focusing on 3 other direct input streams:
USGS Contact 1. Rick Hubbell
- runs the water quality sampling program for DEQ
Helpful for selecting sampling locations to compliment existing monitoring programs and flow gauging sites.
Watershed Nutrient LoadingIN PROGRESS
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Aquatic Ecosystem ModelsRelate Multiple System Responses to Multiple Stressors
Stressors System Responses
Hydrometeorology
Nutrient Loads
Sediment Loads
Habitat ChangesExotic Species Invasions
Toxics Loads
Fish HarvestFish Stocking
Algal biomass & class compositionWater clarity
Fish production, biomassand conditionRelative fish species abundance/harvest
Hypolimnetic DO conditions
Fish body burdens - BCCs
AEMAEM
Feedbacks/Homeostasis
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Adaptive Integrated Framework (AIF): a new methodology for Adaptive Integrated Framework (AIF): a new methodology for managing impacts of multiple stressors in coastal ecosystemsmanaging impacts of multiple stressors in coastal ecosystems
Coupled biophysical 3D models
Empirically based
(Bayesian)
Artificial neural network
Eco
syst
em
Mo
del
s
(e.g. regression)
Simple statistical
• Experimental • Monitoring • Synthesis
Water quality
Human health
Fish
community
dynamics
&
Eco
syst
em
end
po
ints
Recommendations for ecosystem characterization
• Economic models
• Workshops
Socio-economic integration to guide
management
Ecosystem Characterization • Watershed model• Hydrodynamic model• Biophysical data & processes
• Public preference
Ecosystem Stressors
• Land & Resource use
• Climate Change
• Invasive Species
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CSO/SSO Fraction of TP Annual Load to Saginaw Bay
CSO/SSO Est.
(Met. Ton)
WWTP
(Met. Ton.)
Total Load
MDEQ
(Met. Ton)
Total Load
Regr.
(Met. Ton)
CSO’s Fraction of
load
(%)
WWTP Fraction of
load
(%)
2000 1.78 -- -- 278 -- / 0.64 -- / --
2001 2.43 -- 642 412 0.38 / 0.59 -- / --
2002 3.02 -- 513 416 0.59 / 0.73 -- / --
2003 0.59 -- 345 174 0.17 / 0.34 -- / --
2004 2.98 142 724 660 0.41 / 0.45 19.6 / 21.5
2005 -- 146 -- -- -- / -- --/--
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Water Quality Regression Models Based Water Quality Regression Models Based on Flow and Seasonon Flow and Season
Total Phosphorous Loads for Saginaw River (1989-2005)
0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350
Observed Load (g/s)
Est
imat
ed L
oad
(g/s
)
R=0.84
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CSO/SSO Fraction of TP Annual Load to Saginaw Bay
CSO/SSO Est.
(Met. Ton)
Total Load
MDEQ
(Met. Ton)
Total Load
Regr.
(Met. Ton)
Fraction of
MDEQ load
(%)
Fraction of
Regr. load
(%)
2000 1.78 -- 278 -- 0.64
2001 2.43 642 412 0.38 0.59
2002 3.02 513 416 0.59 0.73
2003 0.59 345 174 0.17 0.34
2004 2.98 724 660 0.41 0.45
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CSO and SSO Events in Saginaw Bay CSO and SSO Events in Saginaw Bay (2000-2004)(2000-2004)
Michigan Department of Environmental Quality, 2000-2005
CSOs Events
Wet SSOs Events
Dry SSOs Events
CSOs Discharge
(MGal)
Wet SSOs
Discharge (MGal)
Dry SSOs
Discharge (MGal)
Saginaw 126 85 48 3,766 68.5 14.7
AuGres 0 0 2 0 0 0.018
Pigeon 0 6 7 0 0 0.305
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Water Quality Characterization of CSOs Water Quality Characterization of CSOs and SSOsand SSOs
Fecal Coliform
(M/100 ml)
BOD5 (mg/l)
TSS (mg/l)
TP (mg/l)
TN (mg/l)
Untreated WW/ Dry SSOs
6.4M*
1 M -1 B
120*
88 - 451
206*
118 - 487
5.8
1.3 - 15.7
33
11.4 - 61
Wet
SSOs
500,000 42
6 - 413
91
10 -348
2.0 10*
CSOs 215,000
3 – 40M
43
3.9 – 696
127
1 – 4,420
0.7
0.1 - 20.8
3.6
0 – 82.1
Stormwater 5,081
1 – 5.23M
8.6
0.4 – 370
58
0.5 – 4,800
0.27
0.01 - 15.4
1.4
0.05 – 66.4
Treated WW
<200 30 30 1.65
0.07 - 6
3.95
0.5 - 32United States Environmental Protection Agency, 2004
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Point-SourcesCSO’s and SSO’s
Point-SourcesCSO’s and SSO’s
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91-96 Saginaw Bay Study
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Field Data to Support Lower Food Web Model
• Loads and Forcing Functions– Inflows and lake boundary flows– Nutrient (P, N, Si), sediment and organic carbon loads– Solar radiation and wind
• In situ measurements– Initial conditions for all model state variables– Time and space observations of model state variables
through growing season• Plankton and benthic biomass and group
distribution• Nutrient (various forms and species) concentrations
• Process Experimentation of Value– P budget and internal cycling– Dreissenid particle filtering and nutrient cycling– Sediment nutrient flux rates– Development of empirical light extinction model on
basis of NVSS, Non-algal VSS, Algal VSS, DOM
DePINTO