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Chesapeake Bay Program Incorporation of Lag Times into the Decision Process Gary Shenk 10/16/12 1
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Chesapeake Bay ProgramIncorporation of Lag Timesinto the Decision Process
Gary Shenk10/16/12
2
Chesapeake Bay ProgramDoes Not Incorporate Lag Times
into the Decision Process
3
No Lag in Model or TMDL
• The goal of the TMDL and the Watershed Implementation Plans is to have practices in place by 2025 that will eventually lead to meeting the water quality standards
• Watershed model scenario mode:– The long-term annual average loads given land
use, land management, BMPs, point sources, atmospheric deposition, etc at steady state.
4
Chesapeake Bay Partnership Models
5
Annual, monthly, or daily values of anthropogenic factors:
Land Use AcreageBMPsFertilizerManureTillageCrop typesAtmospheric depositionWaste water treatmentSeptic loads
Hourly or daily values of Meteorologicalfactors:
PrecipitationTemperatureEvapotranspirationWindSolar RadiationDew pointCloud Cover
Daily flow, nitrogen, phosphorus, and sediment comparedto observationsover 21 years
How the Watershed Model Works
HSPF
Calibration Mode
66
Each segment consists of 30 separately-modeled land uses:
• Regulated Pervious Urban• Regulated Impervious Urban• Unregulated Pervious Urban• Unregulated Impervious Urban• Construction• Extractive • Combined Sewer System• Wooded / Open• Disturbed Forest
• Corn/Soy/Wheat rotation (high till)
• Corn/Soy/Wheat rotation (low till)
• Other Row Crops• Alfalfa• Nursery• Pasture• Degraded Riparian Pasture• Afo / Cafo• Fertilized Hay • Unfertilized Hay
– Nutrient management versions of the above
Plus: Point Source andSeptic Loads, and
Atmospheric Deposition Loads Each calibrated to nutrient and
Sediment targets
How the Watershed Model Works
7
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 FLIN
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
SULLIV 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 WILLIA M
GR EE NSV ILLE
MIN ER AL
NEW KE NTGLO U CES TER
KING W ILLIAM
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
WILLIAM 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 FLIN
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
SULLIV 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
SULLIV 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 WILLIA 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 ILLIAM
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
WILLIAM 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
Two Separate Segmentation Schemes• A land use within a land
segment has the same inputs – atmospheric deposition– fertilizer– manure– precipitation
• Land segmentation driven by availability of land use data
• Land segments determined by– County lines– Rainfall Variances– Federal / Non-Federal
Chesapeake Bay Program Modeling
Land Simulation – 1 Acre 4 completely mixed soil layers
Ground Water
Surface
Interflow
Lower Zone
9
Trees
Roots Leaves
ParticulateRefractoryOrganic N
ParticulateLabile
Organic N
SolutionAmmonia
Nitrate
SolutionLabile
Organic N
AdsorbedAmmonia
SolutionRefractoryOrganic N
Storages can Build up in the landscapeA
tmos
pher
ic D
epos
itio
nD
enit
rifi
cati
on
Export
Export Export ExportExport Export Export
10
Precipitation FertilizerManureAtmospheric deposition
Runoff
How the Watershed Model Works
Hydrologysubmodel
Management filter
RiverSedimentsubmodel Phosphorus
submodel
Nitrogensubmodel
}hourly
Scale in Phase 5 - Sediment
BMP Factor
Land Acre Factor
Delivery Factor
Edge of FieldExpected loads from one acre
Edge of Stream60-100 sq miles
In Stream Concentrations
Scour/Deposition
12
Phase 5 river segmentation
• A river segment gathers inputs from the watershed and has one simulated river
• Consistent criteria over entire model domain– Greater than 100 cfs
or– Has a flow gage
13
Constant values of anthropogenic factors:
Land Use AcreageBMPsFertilizerManureTillageCrop typesAtmospheric depositionWaste water treatmentSeptic loads
Hourly or daily values of Meteorologicalfactors:
PrecipitationTemperatureEvapotranspirationWindSolar RadiationDew pointCloud Cover
Run for 1984-2000Average 1991-2000For ‘flow-normalized average annual loads’
How the Watershed Model Works
HSPF
Scenario Mode
1414
20.7 18.9 18.8 18.2 17.8 17.1 16.8 16.8 16.5 13.6
120.0 114.7 109.8 109.2 108.4 106.6 105.7 104.4 103.9 102.8
71.4 71.9
8.25.0
3.5 3.6 4.1 3.5 2.9 2.9 2.9 3.5
2.4 2.4
81.1
59.158.1 56.7 57.7 56.9 56.2 53.7 53.2 54.8
37.1 37.3
7.5
7.77.3 7.1 6.8 6.6 6.6 6.7 6.7 6.6
4.8 4.7
90.5
79.078.4 77.8 75.4 74.4 73.1 73.9 73.8 71.9
52.1 51.4
5.9
5.55.1 5.0 4.9
4.9 4.8 4.6 4.6 4.5
3.0 2.9
175
17 130
50
100
150
200
250
300
350
400
1985 2000 2001 2002 2003 2004 2005 2006 2007 2008 Strategy StateCap
Goal
million lbs.
/year
NY PA DC MD WV VA DE
Nitrogen Loads Delivered to the Chesapeake Bay By Jurisdiction Point source loads reflect measured discharges while
nonpoint source loads are based on an average-hydrology year
333.9
289.9 281.1270.2
175
266.3277.7 275.1
262.9 261.9260.7
184.4 183.1
Phase 4.3 Data
15
Lag Time
• Calibration – the WSM is calibrated to observed data, so including important lagged processes would improve calibration
• Validation of predictions – if the WSM is predicting changes in nutrient loads that are not seen in the monitoring data, would lags help to explain the difference.
• Communication – When will the Chesapeake Bay respond to management actions
