cbp 11/20/01 1 chesapeake bay program modeling past, present, and future chesapeake bay program...
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CBP 11/20/01
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Chesapeake Bay Program Modeling
Past, Present, and Future
Chesapeake Bay Program Office
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The Chesapeake Bay and Watershed
Forest 64%Agricultural 24%Urban 8%Other 4%
Ratio of Areas
Watershed : Estuary ~ 15:1
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Effects of Excess Sediment
Excess sediment can cloud water, block sunlight, and cause SAV to die.
Can damage habitats of somePlants and animals.
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Effects of Excess Nutrients
Excess algae cloud water, block sunlight, and cause SAVto die.
When excess algae die and decompose, they use up oxygen in the water that plants and animalsneed to survive.
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The Chesapeake Bay Program Partnership
Governor of MD
EPA Administrator
Governor of VA Governor of PA
Executive Council
Mayor of DC
Chair of Chesapeake
Bay Commission
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Reduce Nutrient Pollution Loads
As we reduce loads...
…we increase achievement of water quality conditions.
0
50
100
150
200
250
300
350
400
1985 2000 2010
Nu
trie
nt L
oa
d (
mill
ion
lbs/
yr)
nitrogen
phosphorus
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1985 2000 2010DO
Crit
eria
Ach
ieve
men
t (%
wat
er v
olum
e)
% w ater volumeachieving dissolvedoxygen criteria
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Chesapeake Bay Program Management Questions
• What is the estuarine response to reductions of nutrients and sediment?– Water quality (dissolved oxygen)– Living resources (crabs and fish)
• What reductions are achievable?– What to do– Where to do it– Changes in loads from management actions– What are the local effects on riverine water quality?
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Chesapeake Bay ProgramDecision Support System
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
Management Actions
Watershed Model
Bay Model
CriteriaAssessmentProcedures
Effects
Allocations
Airshed Model
Land UseChange Model
ScenarioBuilder
Sparrow
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Chesapeake Bay ProgramDecision Support System
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
Management Actions
Watershed Model
Bay Model
CriteriaAssessmentProcedures
Effects
Allocations
Airshed Model
Land UseChange Model
ScenarioBuilder
Sparrow
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Watershed Model
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Snapshot:
Land Use AcreageBMPsFertilizerManureAtmospheric DepositionPoint SourcesSeptic Loads
Hourly Values:
RainfallSnowfallTemperatureEvapotranspirationWindSolar RadiationDewpointCloud Cover
“Average AnnualFlow-Adjusted Loads”
Quick Overview of Watershed Model Scenarios
Hourly output is summed over 10 years of hydrology to compare against other management scenarios
HSPF 1991-2000
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Each segment consists of separately-modeled land uses
• High Density Pervious Urban• High Density Impervious Urban• Low Density Pervious Urban• Low Density Impervious Urban• Construction• Extractive • Wooded• Disturbed Forest
• Corn/Soy/Wheat rotation (high till)
• Corn/Soy/Wheat rotation (low till)
• Other Crops• Alfalfa• Nursery• Pasture• Degraded Riparian Pasture• Animal Feeding Operations• Fertilized Hay • Unfertilized Hay
– Nutrient management versions of the above
Plus Point Source and Septic
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Agriculture40%
Forest15%
Atmospheric Deposition to Non-
Tidal Water1%
Urban & Suburban Runoff18%
Municipal & Industrial
Wastewater21%
Septic5%
Agriculture - manure19%
Agriculture - chemical fertilizer
16%
Agriculture - Atmospheric Deposition - livestock & fertilized soil
emissions6%
Atmospheric Deposition - mobile (on-road + non-
road) + utilities + industries
21%
Natural - lightning + forest soils
1%
Urban & Suburban Runoff - chemical
fertilizer11%
Municipal & Industrial Wastewater
21%
Septic5%
Land Use of origin
SourceDifferent Types of Load Allocations to
Sources
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From the Chesapeake Bay Commission Report: Cost-Effective Strategies for the Bay
December, 2004
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Number of segment / land-use / years in watershed model
100
1000
10000
100000
1000000
1980 1985 1990 1995 2000 2005 2010
Year of completion
op
era
tio
ns
Watershed Model History
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First Version of the Watershed Model:
• Completed in 1982.
• 63 model segments.
• 2 year calibration period (Mar.- Oct.).
• 5 land uses.
• IBM mainframe platform.
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Primary Products of the First Version of the Watershed Model:
First estimate of relative point source and NPS loads for each major basin.
Demonstration of the importance of controlling NPS loads in the Chesapeake.
"Framework for Action" report, the first basin by basin assessment of Chesapeake nutrient loads.
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Second Version of the Watershed Model - Phase 2:
•Completed in 1992.
•63 model segments.
•4 year calibration period (1984-87).
• 9 land uses.
• DEC VAX mainframe platform.
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Primary Products of Phase 2:
• First nitrogen and phosphorous allocations for each major basin.
• First linkage to water quality model of the estuary.
• First linkage to the airshed model (RADM) and estimates of atmospheric loads for each major basin.
Base Case 40% Controllable LOT
Key Phase 2 Scenarios
0
50
100
150
200
250
TN
- M
illions o
f P
ound
s
NPSPSAtmosphere
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Third Version of the Watershed Model - Phase 4:
• Completed in 1998.
• 94 model segments.
• 9 land uses.
• 14 year calibration period (1984-97) using automated input and output model processors.
• Cray, DOS, Solaris, and linux platforms.
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Primary Products of Phase 4:• Nutrient Allocations in 2000 (p4.1)
• Nutrient Allocations in 2003 (p4.3)
• Began open source, public domain, web distribution of preprocessors, post processors, and open source code. First download and use by non-CBP.
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Fourth Version of the Watershed Model - Phase 5:
• 1,063 model segments.
• 21 year calibration period (1985-2005).
• 24 land uses using• time-varying land use & BMPs.
• Open source, public domain, distributed over the web:http://ches.communitymodeling.org/models/CBPhase5/index.php• Purpose: TMDL
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Automated Calibration
CalibrationProcedures
Input Data
“Scenario builder”
CalibrationData
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Phase 5 – A Ten Fold Increase in Segmentation Over Previous Phase 4.3 Model
ELK
TIOG A
ON EID A
YO RK
KEN T
STEU BE N
SUS SE X
HER KIM E R
PO TTER
DELA WA RE
BER KS
OTS EG O
MC KE AN
ACC O M AC K
IND IAN A
WAY NE
HALIF AX
ALLEG AN Y
SO M ERS ET
LE E
CLEA RFIE LD
CAY UG A
BLAIR
LU ZE RN E
BRA DF OR D
CEN TR E
LA NC AS TER
PER RY
BRO O M E
CH EST ER
CH EN ANG O
SUR R Y
CAM B RIA
ST M AR YS
CLIN TO N
ON TAR IO MA DIS ON
CEC IL
DO RC H ESTE R
LO U ISA
PITTS YLVA NIA
ON O ND AG A
GA RR ETT
CH AR LES
WISE
SCO TT
PRE STO N
HU NTIN G DO N
LY CO M IN G
BED FO RD
SCH U YLKILL
GU ILFO RD
FRA NK LIN
TALBO T
WYT HE
BALTIM O R E
FAU QU IER
FLOY DSM YTH
YATE S
HEN R Y
STO KE S
AUG U STA
JE FFER SO N
BATH
HAR D Y
FULTO N
HAM P SH IRE
BLAN D
ALBE MA RLE
SUS Q UEH AN N A
ADA M S
MIF FL IN
HAR FO RD
MO N RO E
WO RC ES TER
LIV ING S TON
CAR O LINE
SCH O HA RIE
CR AIG
LO U DO U NTUC KE R
NO RT HAM P TO N
WAR R EN
AM ELIA
FAIR FAX
PER SO N
HAN O VER
CAR R OLL
GR AN VILLE
CAM P BELL
JU NIA TA
TOM P KIN S
CO LUM B IA
DIN WID DIE
SULL IV AN
SUF FO LK
OR AN G E
MC D OW ELL
BRU N SWIC K
CO RT LAND
CAR BO N
BUC H ANA N
ASH E
NELS O N
CAS WE LL
ME CK LEN BU RGPATR IC K
FOR SY TH
BUC KIN G HA M
ESS EX
RO CK ING H AM
RU SSE LL
DAU PH IN
TAZE WELL
GR AN T
SNY DE R
CH EM UN G
ALAM AN C E
CH AR LOTT E
PULA SKI
BO TETO U RT
VAN CE
CAM E RO N
SO UTH AM P TON
RO CK BR IDG EALLEG HA NY
WAS HIN G TO N
LE BA NO N
AM HE RS T
NEW C ASTLE
ANN E A RU ND EL
CALV ER T
WIC OM IC O
FRE DE RIC K
CU LPEP ER
QU EE N AN N ES
LU N EN BUR G
MO N TG OM E RY
PAG E
LA CK AW AN NA
SCH U YLER
JO H NS ON
WAT AU GA
BER KE LE Y
VIRG IN IA BE AC H
CU M BER LAN D
WYO M IN G
PEN DLE TO N
CH EST ERF IELD
DIC KEN SO N
UN ION
HO WA RD
PRIN C E G EO RG ES
FLUV ANN A
NO TTO WA Y
SPO TS YLVA NIA
HEN R ICO
GR AY SO N
STAF FOR D
CH ESA PEA KE
MO R G AN
HIG HLA ND
SHE NA ND O AH
MA TH EWS
NO RT HU M BER LAN D
GILE S
APP OM A TTO X
ISLE O F W IGH T
GO O CH LAN D
PO WH ATA N
CLAR KE
PRIN C E WILL IA M
GR EE NSV ILLE
MIN ER AL
NEW KE NTGLO U CES TER
KING W ILL IAM
PRIN C E ED WA RD
RIC HM O ND
KING A ND QU EE N
MID D LESE X
RO AN O KE
PRIN C E G EO RG E
JA M ES C ITY
WES TM O RE LAND
CH AR LES C ITY
KING G EO R GE
HAM P TO N
MO N TO UR
NO RF OLK
RAP PA HAN N OC K
GR EE NE
NEW PO R T NE WSPO QU O SO N
BO TETO U RT
DAN VILLE
LY NC HB UR G
DIST OF CO LUM B IA
PO RTS M OU THBRIS TO L
HAR R ISO NB UR G
RAD FO RD
WAY NE SBO R O
HO PE WELL
MA NA SSA S
NO RT ON
EM PO RIA
FRE DE RIC KSB UR G
WILL IAM S BU RG
BUE NA VIST A
SO UTH BO ST ON
ARLIN G TO N
SALE M
STAU N TON
PETE RS BU RG
GA LAX
ALEX AN DR IA
MA RT INSV ILLE
WIN CH EST ER
CH AR LOTT ESV ILLE
FAIR FAX CITY
CO LO NIAL H EIG H TS
CO VIN G TONLE XIN G TON
CLIFTO N FO RG E
FALLS C HU R CH
MA NA SSA S P ARK
ELK
TIOG A
ON EID A
YO RK
KEN T
STEU BE N
SUS SE X
HER KIM E R
PO TTER
DELA WA RE
BER KS
OTS EG O
MC KE AN
ACC O M AC K
IND IAN A
WAY NE
HALIF AX
ALLEG AN Y
SO M ERS ET
LE E
CLEA RFIE LD
CAY UG A
BLAIR
LU ZE RN E
BRA DF OR D
CEN TR E
TIOG A
LA NC AS TER
PER RY
BRO O M E
CH EST ER
CH EN ANG O
KEN T
SUR R Y
CAM B RIA
ST M AR YS
CLIN TO N
ON TAR IO MA DIS ON
CEC IL
DO RC H ESTE R
LO U ISA
PITTS YLVA NIA
ON O ND AG A
GA RR ETT
CH AR LES
WISE
SCO TT
PRE STO N
HU NTIN G DO N
LY CO M IN G
BED FO RD
SCH U YLKILL
GU ILFO RD
FRA NK LIN
TALBO T
SUS SE X
WYT HE
BALTIM O R E
FAU QU IER
FLOY DSM YTH
YATE S
HEN R Y
STO KE S
AUG U STA
JE FFER SO N
BATH
HAR D Y
FULTO N
SO M ERS ET
HAM P SH IRE
BLAN D
ALBE MA RLE
SUS Q UEH AN N A
ADA M S
MIF FL IN
HAR FO RD
MO N RO E
WO RC ES TER
LIV ING S TON
CAR O LINE
SCH O HA RIE
CR AIG
LO U DO U N
LY CO M IN G
TUC KE R
NO RT HAM P TO N
CEN TR E
WAR R EN
AM ELIA
FAIR FAX
FRA NK LIN
PER SO N
HAN O VER
CAR R OLL
GR AN VILLE
CAM P BELL
CAR R OLL
JU NIA TA
TOM P KIN S
CO LUM B IA
DIN WID DIE
SULL IV AN
SUF FO LK
OR AN G E
MC D OW ELL
BRU N SWIC K
BED FO RD
CO RT LAND
BATH
CAR BO N
BUC H ANA N
ASH E
SULL IV AN
NELS O N
SUR R Y
CAS WE LL
ME CK LEN BU RGPATR IC K
FOR SY TH
BUC KIN G HA M
ESS EX
RO CK ING H AM
RU SSE LL
DAU PH IN
TAZE WELL
GR AN T
SNY DE R
CH EM UN G
ALAM AN C E
OR AN G E
CH AR LOTT E
PULA SKI
BO TETO U RT
VAN CE
CAM E RO N
SO UTH AM P TON
RO CK BR IDG E
YO RK
ALLEG HA NY
WAS HIN G TO N
LE BA NO N
AM HE RS T
NEW C ASTLE
ANN E A RU ND EL
CALV ER T
WIC OM IC O
FRE DE RIC K
AUG U STA
FRE DE RIC K
RO CK ING H AMCU LPEP ER
NO RT HAM P TO N
QU EE N AN N ES
LU N EN BUR G
MO N TG OM E RY
PAG E
ASH E
WAS HIN G TO N
LA CK AW AN NA
SCH U YLER
CAR O LINE
JO H NS ON
WAT AU GA
BER KE LE Y
VIRG IN IA BE AC H
CU M BER LAN D
FRA NK LIN
BED FO RD
CLIN TO N
BED FO RD
WYO M IN G
PEN DLE TO N
CH EST ERF IELD
HAR D Y
GR AN T
DIC KEN SO N
PEN DLE TO N
UN ION
HO WA RD
PRIN C E G EO RG ES
FLUV ANN A
NO TTO WA Y
SPO TS YLVA NIA
MO N TG OM E RY
HEN R ICO
GR AY SO N
STAF FOR D
CH ESA PEA KE
MO R G AN
HIG HLA ND
SHE NA ND O AH
MA TH EWS
NO RT HU M BER LAN D
GILE S
APP OM A TTO X
ISLE O F W IGH T
ALLEG AN Y
MA DIS ON
PAG E
GO O CH LAN D
RO CK ING H AM
PO WH ATA N
CLAR KE
LE E
PRIN C E WILL IA M
GR EE NSV ILLE
FRE DE RIC K
CU M BER LAN D
GILE S
DAU PH IN
MIN ER AL
NEW KE NT
UN ION
GLO U CES TER
KING W ILL IAM
PRIN C E ED WA RD
ADA M S
RIC HM O ND
LA NC AS TERKING A ND QU EE N
GR AY SO N
MID D LESE X
JE FFER SO N
RO AN O KE
ALLEG AN Y
PRIN C E G EO RG E
BRA DF OR D
GILE S
MIN ER AL
HIG HLA ND
JA M ES C ITY
ALLEG HA NY
WES TM O RE LAND
BED FO RD
NO RT HU M BER LAN D
CH AR LES C ITY
WAR R EN
NELS O N
KING G EO R GE
HAM P TO N
MO N TO UR
SCO TT
PATR IC K
MA DIS ON
SHE NA ND O AH
RU SSE LL
AM HE RS T
WYO M IN G
NO RF OLK
AUG U STA
RAP PA HAN N OC K
GR EE NE
WAR R EN
LU ZE RN E
CU M BER LAN D
FRA NK LIN
TAZE WELL
SM YTH
GR EE NE
BALTIM O R E
SCO TT
ALBE MA RLE
RO AN O KE
NEW PO R T NE WSPO QU O SO N
RIC HM O ND
RAP PA HAN N OC K
BO TETO U RT
ALLEG HA NY
DAN VILLE
FAU QU IER
RO AN O KE
LY NC HB UR G
WYT HE
CAR R OLL
DIST OF CO LUM B IA
PO RTS M OU THWAS HIN G TO N
PETE RS BU RG
BRIS TO L
RAD FO RD
WAY NE SBO R O
HO PE WELL
MA NA SSA S
EM PO RIA
BED FO RD
FRE DE RIC KSB UR G
WILL IAM S BU RG
SO UTH BO ST ON
CH EST ER
RO CK BR IDG E
RO CK ING H AM
ARLIN G TO N
SALE M
STAU N TON
GA LAX
ALEX AN DR IA
HAR R ISO NB UR G
NO RT ON
FRA NK LIN
MA RT INSV ILLE
WIN CH EST ER
CH AR LOTT ESV ILLE
BUE NA VIST A
FAIR FAX CITY
CO LO NIAL H EIG H TS
CO VIN G TONLE XIN G TON
CLIFTO N FO RG E
FALLS C HU R CH
MA NA SSA S P ARK
Phase 4.3 land and river segments Phase 5 land segments Phase 5 river segments
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A software solution was devised that directs the appropriate water, nutrients, and sediment from each land use type within each land segment to each river segment
ExternalTransferModule
Each land use type simulation is completely independent.Each river simulation is dependent on the local land use type simulations and the upstream river simulations.
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Land variableWDM
Final TextOutput
River variableWDM
METWDM
ATDEPWDM
PSWDM
ExternalTransferModule
Land Input File Generator
River Input File Generator
WDM = HSPF-specific binary file typeUCI = User Controlled Input (input file)
1
2 3 5
6
4
1. Land UCIs are generated2. HPSF is run on the land UCIs and output is stored in individual WDMs3. The ETM is run converting land output to river input, incorporating land use, BMPs, and
land-to-water delivery factors. Output is stored in river-formatted WDMs4. River UCIs are generated5. HSPF is run on the river UCIs and output is written back to WDMs6. Postprocessor reads river WDMs and writes ASCII output
Flexible Functionality
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ScenarioBuilder
ScenarioInput Files
Manure, Fertilizer, Legume, Uptake,
Crop Cover,Land use, BMP type,
BMP acreage
Meteorological and
Precipitation Data
CMAQAtmospheric
Output
Atmospheric Deposition
Data
Meteorological, Precipitation, and
Atmospheric Deposition WDMs
ScenarioInput Files
Septic, Point
Sources
Data to WDM
processing Programs
DiversionsData
Point Source, Septic, and Diversion
WDMS
HSPF Parameter
Files
CBPSoftware
ExogenousData
Internal ASCII Data
Internal Binary Data
Land UCI Generator
(LUG)1-7392
independent 1-3 second
runs
Internal or Exogenous
Data
Land Control Files
Geographic Specification
Files
I/O Variable Specification
Files
Land UCIs
Chesapeake Bay Program Watershed Model Phase 5 Software
Echo InputsOutput Data
HSPF1-7392
independent3-8 second
runs
Land Variable WDMs
.out filespltgens
.ech files
River UCI Generator
(LUG)1-7392
independent 1-3 second
runs
River UCIs HSPF1-738
independent3-8 second
runs
River Variable WDMs
.out files pltgens.ech files
River Control Files
UpstreamWDMAdder
Edge-of-Stream River Input Variable
WDMs
External Transfer Module
Text Output
WQM input generator
WQM input
PostProcessor
Land Calibration
Update Program
Calibration control Files
Calibration Targets
Calibration Rules
Observed Data
Hydrology Calibration
Update Program
River Water Quality
Calibration Update
Program
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Scenario Builder
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Chesapeake Bay ProgramDecision Support System
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
Management Actions
Watershed Model
Bay Model
CriteriaAssessmentProcedures
Effects
Allocations
Airshed Model
Land UseChange Model
ScenarioBuilder
Sparrow
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Number of Scenarios
• Phase 1 – 0
• Phase 2 – fewer than 10
• Phase 3 – never used
• Phase 4.1 – 37
• Phase 4.3 – 400-500
• Phase 5 – about 30 pre-finalization– Lauren Hay plans to run 600– 1000s? For management
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Watershed Wide Crops by Acreage
21.5%
9.1%
14.8%
11.7%
25.7%
11.9%
1.8%
1.2%0.3%
0.8%
0.3%
0.9%
2.4%
Corn & Sorghum (Grain) Corn & Sorghum (Silage) Soybeans Small Grains
Other Hay Alfalfa Vegetables Harvested Berry & Orchard
Potatoes Tobacco Cotton Peanuts
Approximately 100 crop types and 10 growing regions with different parameters for each
Tracking yields and acreages on a county basis
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Manure Data Model
Pasture
Beef
Uncollected
Collected
Spring/FallApplication
Daily Application
Crop
Enclosure
Barnyard
Volatilization
Volatilization
Daily Application
Storage
VolatilizationVolatilization
Volatilization
Runoff Runoff
DairySwineLayersBroilersTurkeys
Transport
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Fertilizer Sold
Manure Mass-balance
Non-NM acres w/ all
leftover fertilizer
Non-NM acres w/ leftover manure
starter fertilizer, with manure applied after
Manure on NM acresAcres of crop w/o manure
Volatilized fertilizer
NH3 NM crops w/o
manure
NM acres w/ manure
Non-NM acres
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Scenario Builder
AKA COASTAKA Vortex
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Chesapeake Online Assessment Support Tool
Observed Data and Calculated Trends
Select Your WatershedChoose your task
Scenario Builder
View loads spatially
View Factors Affecting Trends
Product of USGS and CBPO
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Estuarine Model
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Chesapeake Bay ProgramDecision Support System
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
Management Actions
Watershed Model
Bay Model
CriteriaAssessmentProcedures
Effects
Allocations
Airshed Model
Land UseChange Model
ScenarioBuilder
Sparrow
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ThreeAlgal
Groups
Microzooplankton
DissolvedOrganicCarbon
LabileParticulate
OrganicCarbon
RefractoryParticulate
OrganicCarbon
Mesozooplankton
ExternalLoads
InorganicCarbon
Sediments
Respiration
RespirationRespiration
Carl CercoUSACE - ERDC
CBP 11/20/01
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The 1987 Model
• 3-D hydrodynamics and water quality.
• Summer, steady-state.• Indicated the
importance of sediment-water interactions.
• One part of decision process that concluded a 40% nutrient load reduction would eliminate anoxia.
1985 grid, 585 cells
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Three-D Time Varying Model (1992)• Linked watershed,
hydrodynamic, and eutrophication models.
• Dynamic benthic sediment diagenesis component.
• Continuous application 1984-1986 and 1959-1988.
• Guided 1991 re-evaluation of 1987 Chesapeake Bay Agreement.
1992 grid, 5000 cells
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Tributary Refinements 1997• 10,000 cell grid.• Intertidal
hydrodynamics.• Ten-year simulation
1985-1994.• Direct simulation of
living resources.
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Tributary Refinements 1997
• Move boundary out to continental shelf.
• Introduce suspended solids.
• Relate light attenuation to suspended solids.
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Added Living Resources 2003
• 13,000 cells
• Mesozooplankton
• Microzooplankton
• Submerged Aquatic Vegetation
• Filter Feeding Benthos (three species)
• Deposit-Feeding Benthos
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ThreeAlgal
GroupsMicrozooplankton
DissolvedOrganicCarbon
LabileParticulate
OrganicCarbon
RefractoryParticulate
OrganicCarbon
Mesozooplankton
ExternalLoads
InorganicCarbon
Sediments
Respiration
RespirationRespiration
Carbon Cycle
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Epiphytes Phytoplankton
SAV ShootsDissolved Nutrients
Particulate Nutrients
SAV RootsDissolved Nutrients
Particulate Nutrients
Water Column
Sediments
Submerged Aquatic Vegetation Model
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Particulate Organic Matter
Dissolved Nutrients
Dissolved Oxygen
FilterFeeders
Particulate Organic Matter
DepositFeeders
Dissolved Nutrients
OxygenDemand
respiration
filt
rati
on
se
ttli
ng
bio
de
po
sit
s
fee
din
g
se
dim
en
t-w
ate
r
e
xc
ha
ng
e
excretion
se
dim
en
t-o
xy
ge
n
de
ma
nd
respiration
excretion
diagenesis
diagenesis
WaterColumn
Sediments
Benthic submodel
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The 2008 Model
• 57,000 total cells.• Process-oriented
suspended solids model with ROMS bed.
• Advanced optical model.
• oyster model.• Menhaden model
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8400 Oyster Bars
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Linkages to outside models
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Chesapeake Bay ProgramDecision Support System
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Percent of Space
Per
cent
of T
ime
CFD Curve
Area of Criteria Exceedence
Area of AllowableCriteria
Exceedence
Management Actions
Watershed Model
Bay Model
CriteriaAssessmentProcedures
Effects
Allocations
Airshed Model
Land UseChange Model
ScenarioBuilder
Sparrow
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Climate Change Model
• EPA office of climate change supplied down-scaled climate change output
• Linked to rainfall model and watershed model.
Source: Frumhoff et al. 2006 Climate change in the NE United States
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Watershed ModelInput DataChesapeake Bay Land
Change Model
GrowthAllocation Model“GAMe”
COG and MDPDemographic
&Employment
Forecasts
FutureUrban Area
Seweroutflows
Septicloads
Sewer Model
Sewer ServiceAreas
1990 Impervious Surface
and2000 Impervious
Surface
CalibrationMetrics
Cellular Automata
Model“CB-SLEUTH”
Slope,Protected
lands,Zoning,
Priority FundingAreas
Land Use/Land Cover
(NLCD)
Proportions offarm and forest
converted
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487 daily stations192 hourly stations
Monthly Regression of LatitudeLongitudeAltitude
Daily Intercept
Rainfall
1984-2005
Lauren Hay – USGS NRP
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Atmospheric Deposition Estimates
Combining a regression model of wetfall deposition...
…with CMAQ estimates of dry deposition for the base…
…and using the power of the CMAQ model for scenarios.
Jim Lynch, Jeff GrimmPenn State
Robin Dennis, EPA/NOAA
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The Community Multiscale Air Quality Model (CMAQ) has a domain that covers the North American continent at a 36 km x 36 km grid scale and is nested at a finer 12 km x 12 km grid scale over the Chesapeake watershed and Bay.
CMAQ Model
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Mostly ad hoc, hard coded
• CMAQ watershed model
• Rainfall watershed model
• Land change models scenario builder
• Estuarine model outputs
• Scenario Builder watershed model– But could easily be fit to a standard
57
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Watershed – Estuarine coupling
• Not a particular standard, but very flexible.• Geography file• Transcription of Variables file• Uses so far
– 13k estuarine model– 57k estuarine model– 4k estuarine model (CBEO)– Potomac TMDL– York TMDL– SERC Study– UMD study
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Watershed model is actually a coupled system of models
• 24 X 308 land models• 700 river models• Translation models• Examples of modularity
– Mass-balance and coefficient-based land nutrient models running simultaneously
– Some urban models swapped for CSO data– Reservoir operations models inserted
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Crystal Ball
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Scenario Builder Future
• Within the next year– Finish building– Create web-based GUI– Port to grid
• Longer Term– Interface with other models?– Automated data gathering?– Integrate with EPA’s BASINS?– Use for a different study area?
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Watershed Model future• Near Future
– Port to grid– Uncertainty analysis– Substitute models
• Different river simulation?• Small-scale agricultural models?
– Expand geographic area?
• Longer Term– Evolve on phase 5 framework
• or
– Move to distributed
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Uncertainty Analysis
Real Data (ag census)(BMP implementation #s)
Assumptions or model
HSPF
Calibration Theory
Bay Model
WQStandards
Method
AllocationMethod
WSM
Calibrationskill
Model Inputs
Parameters
Desired State of Real Data(ag census)
(BMP implementation #s)
Multiple ModelDecision UncertaintyAnalysis
Purple – independent variable
Red – dependent variable
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Water Quality Model
Coupling the Ecopath with Ecosim ecological model to the Water Quality Model will examine the interaction between habitat and living resources.
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Current questions
• Has the assimilation capacity changed (Hagy hypothesis)
• What is the interaction between water quality and living resources
• Refine factors that predict nutrient and sediment runoff from land sources including management practices.
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Questions requiringshort-term modeling
• Are the fish safe to eat?
• Can we swim?
• What will the current be tomorrow?
• Are the fish biting?
• Will there be jellyfish tomorrow?
• Will my city flood when the hurricane comes?