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1
Identifying Stressors, Sources, and Needed PollutantLoad Reductions
Stephen Carter, PE
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
2
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
3
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
4
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
Pollutant Sources and Impacts
Pollutants• Nutrients• Sediment• Pathogens• Temp• Salt• Metals• Pesticides• Organics
Point Sources• WWTP• Urban runoff• Industry
Nonpoint Sources• Forest/natural runoff• Streambank erosion• Reduced shading• Atmospheric deposition• Abandoned mines• Construction• Agriculture
• Cropland• CAFOs
Impacts• Aquatic life• Habitat• Fishing & swimming• Human health• Nuisance odors• Algal blooms
5
The Technical Approach
Establish a link between watershed sources and receivingwater responses to represent cause-effect relationships
Sources
Loading Receiving Water Response
Keep in mind…it’s not the approach itself, but how you put it all togetherthat achieves the objectives.
What is a Model?
• A theoretical construct,• together with assignment of numerical values to model
parameters,• incorporating some prior observations drawn from field and
laboratory data,• and relating external inputs or forcing functions to system
variable responses
* Definition from: Thomann and Mueller, 1987
6
What Constitutes a Model?
Input Model Output
Factor 1
Rainfall Event
Pollutant Buildup
Others
Land use
System
Soil
Stream
Pt. Source
Factor 2
Factor 3
Response
Common Questions Regarding the Use of Models
Is a model necessary?
Which model should I use?
What are the trade-offs between using simple and complex models?
Which features of the system should the modeling efforts focus on?
How can modeling results be integrated into the overall watershedplanning framework?
How can complex model results be effectively transmitted to thepublic?
What else, besides models, can I use?
7
Role of Modeling in Decision Making
Indicators ManagementSystem1
2
3
4
• Alternatives evaluation/design support• TMDLs• Watershed management• Permits• Hazardous waste remediation• Harbors• Stormwater• New development
Modeling in Decision Making
Types of analysis
Waterbody Type
Inputs
Land River Lake Estuary
Environmental Factors: Precipitation, Temperature, Solar RadiationEnvironmental Factors: Precipitation, Temperature, Solar Radiation
Management Practices, Water Withdrawals, Waste InputsManagement Practices, Water Withdrawals, Waste Inputs
Ocean
8
Model Categories
Landscape/Loading models Runoff of water and dissolved materials on and through the land
surface Erosion of sediment and associated constituents from the land
surface
Receiving water models Flow of water through streams and into lakes and estuaries Transport, deposition, and transformation in receiving waters
Watershed models Combination of landscape and receiving water models
Model Categories
Landscape/Loading models
Crops
Pasture
Urban
Watershed models
Crops
Pasture
Urban
Receiving water models
9
Model Basis
Empirical Formulations
mathematical relationship based on observed datarather than theoretical relationships
Deterministic Models
mathematical models designed to produce systemresponses or outputs to temporal and spatial inputs
Level of Complexity – Landscape Models
Export Coefficients
average annual unit area loads based on landuse type
Loading Functions
simplified erosion and water quality loading combinedwith basic representation of hydrologic processes
Dynamic Models
mechanistic (process-based), time-variablerepresentation of watershed processes, includinghydrology, erosion, and water quality
Incre
ase
dC
om
ple
xity
10
Level of Complexity - Receiving Water Models
Steady-state Models
fate and transport model that uses constant values of inputvariables to predict constant results (under a representativecondition)
Quasi-dynamic Models
similar to steady-state formulations, but may include diurnalrepresentation
Dynamic Models
mathematical formulation describing the physical behavior of awaterbody and its temporal variability
• Hydrodynamic - circulation, transport, deposition
• Water Quality - nutrients, toxics, pathogens, etc.
Incre
ase
dC
om
ple
xity
ModelingApproach
GoverningProcesses
TimeScale
SpatialScale
Model Testing
The Modeling Dilemma
11
Governing Processes
Input Algorithms Output
Time seriesMeteorologyStreamflow
WQ sampling
Spatial/LandscapeSoils
TopographyLand cover
Pollutant characteristics
Receiving WatersPhysical data
Kinetics data
Fate & transport
Landscape/Watershed Models
HydrologyBuildupWashoffErosion
Overland transportFate & transport
Receiving WaterModelsHydraulics
HydrodynamicsFate & transport
Scour & depositionChemical interactions
Time seriesSummary statistics
% change/Improvement
ViolationsClassification maps
Impact maps
GoverningProcesses
Time Scale SpatialScale
Model Testing
?
Governing ProcessesHow to reduce the level of effort?
Structured selection should lead to the simplestmodel
Simplification of processes
Preserve the sensitivity of the model
Preserve the response of cause-effect relationships
Level of calibration
Gross estimates
Comparative analyses
Design
12
Governing ProcessesWet vs. Dry Conditions
Wet conditions
Episodic
Dynamic
Dry conditions
Sustained flows overdry periods (e.g.,urban runoff, POTWeffluent)
Requires modelingassumption (e.g.,steady state)
FC vs. Flow at Mouth of San Diego River
0
50
100
150
200
250
300
350
400
J-99 M-99 A-99 D-99 A-00 A-00 D-00 A-01 A-01
Date
Str
ea
mF
low
(cfs
)
1
10
100
1000
10000
100000
FC
(MP
N/1
00
mL
)
Time ScaleWatershed Model
Landscape/Watershed
Representative time period (capture
range of hydrologic conditions - dry
and wet years, critical events)
Representative time step
• Long-term seasonal and annualaverages
• Relative comparison analysis
• Assimilative capacity and standards
GoverningProcesses
Time Scale Spatial Scale
Model Testing
?
13
Time ScaleReceiving Water Model
Receiving Water
Representative time period (capture range of
hydrodynamic conditions – dry/wet years, critical events)
Representative time step
• Model processes (eutrophication, sediment diagenesis)
• Relative comparison analysis
• Assimilative capacity and standards
GoverningProcesses
Time Scale Spatial Scale
Model Testing
?
Spatial ScaleConsiderations
Basin-wide loading estimates R/WS/SWS
“Program” development andimplementation WS/SWS/SAM
Pollution control design SAM
Analysis of receiving waterquality impairment RW, SAM
Credits for BMP implementation SAM, RW
• Regional (R)• Watershed (WS)• Sub-watershed (SWS)• Small area mgmt (SAM)• Stream segment/
receiving water (RW)
• Regional (R)• Watershed (WS)• Sub-watershed (SWS)• Small area mgmt (SAM)• Stream segment/
receiving water (RW)
GoverningProcesses
TimeScale Spatial
Scale
Model Testing
?Scale
14
Model Testing
GoverningProcesses
Time Scale Spatial Scale
Model Testing
?
1. CALIBRATION: model parameter adjustment or fine-tuning toreproduce observation data
2. VALIDATION: testing of calibration adequacy through applicationof parameters to an independent data set (without furtheradjustment)
3. VERIFICATION: examination of the numerical technique in thecomputer code to ascertain that it truly represents the conceptualmodel and that there are no inherent numerical problems
Location and Time Period Selection
Calibration
monitoring data availability
proximity to area of interest
range of hydrologic and water quality-associatedconditions
Validation
separate time period
different location
monitoring data availability
15
Example: Calibration/ValidationTime Period Selection
Time
Calibration ValidationSetup
Example: Calibration/Validation Location Selection -Watershed Model
Calibration Location
Validation Location
16
Uncertainty in Modeling Analysis
Data limitations
Science limitations
Cost & Time = ModelConstraints Uncertainty+
Measures of Analysis Uncertainty
0
20
40
60
80
J-97 J-98 J-99 J-00
Month
Flo
w(c
fs)
0
2
4
6
8
10
12
14
Month
lyR
ain
fall
(in)
Avg Monthly Rainfall (in)
Avg Observed Flow (1/1/1997 to 12/31/2000 )
Avg Modeled Flow (Same Period)
17
Challenges in Evaluating Uncertainty
1 2 3 4 5
All
ow
ab
leLo
ad
ing
?
Time
Typical Points of Contention
Don’t like the conclusions
Speed/time insufficient to comment or provide input
Concerns over data quality/data sufficiency
“bad” science
Inability of agency to respond to comments
Equity of management cost responsibilities
Clarity of conditions for future adaptation or update
18
Tools for Resolution
Early buy-in on methods
Engaged stakeholders
Targeted data collection
Communication
Proactive response to comments
Consideration of alternative allocations
Consideration of cost
Flexibility in schedule
Clear options for update or future revision
Factors to Consider in Selecting Level ofAnalysis
Available dataAvailable timeAvailable LOE
Value of resourceCost implications of allocationEnvironmental risk of allocation
Technical complexityLevel of detail
What can you afford?
What happens when you allocate?
How carefully must specific processes be represented?
19
Each issue requires different analytical techniques
Considerations—Pollutant/Stressor
Eutrophication/Algal Bloom
Nutrient enrichment
Oxygen depletion
Sediment diagenesis of organic matter
Sediment transport problems
Toxic contamination
Pathogen contamination
Thermal problems
Others
Considerations—Waterbody Type
Rivers and Streams relatively fast flowing
variable residential time
transport processes are usually dominant
Lakes and Reservoirs slow moving water
deposition and accumulation processes
recycling processes
both acute and delayed responses
Estuaries reversal flows and tidal influences
20
Each source requires different modeling techniques
Considerations—Sources
Constant loading: A large wastewater plant
Variable or intermittent loading: An industrial facility
Randomly occurring loading: Rainfall driven loads -NPS, stormwater
Considerations—Water Quality Standards
Numeric endpoint
Narrative criteria
Seasonal variation
Dependency on another constituent
Averaging period (chronic versus acute)
21
Steady State condition
Cumulative condition
Episodic condition
Considerations—Impairment Conditions
Steady State Condition
Prolonged response
Critical condition can be represented by
constant flow rate (design flow)
Impairment usually occurs at low flow
Represent well most PS problems
22
Willow Run - West
Prophecy Creek
Wises Mill Trib.
Valley Rd. Trib.Monoshone Creek
Creshiem Creek
Paper Mill Run
Sandy Run
Pine Run
Rose Valley Trib.
Willow Run - East
Trewellyn Creek
Lorraine Run
MONTGOMERY CO.
PHILADELPHIA CO.County BoundariesWissahickon WatershedReach File, V3303(d) Listed Segments: Nutrients
Wissahickon Creek
N
2 0 2 4 Miles
Data Sources:PA DEPU.S. EPA BASINS
Willow Run - West
Prophecy Creek
Wises Mill Trib.
Valley Rd. Trib.Monoshone Creek
Creshiem Creek
Paper Mill Run
Sandy Run
Pine Run
Rose Valley Trib.
Willow Run - East
Trewellyn Creek
Lorraine Run
MONTGOMERY CO.
PHILADELPHIA CO.County BoundariesWissahickon WatershedReach File, V3303(d) Listed Segments: Nutrients
Wissahickon Creek
N
2 0 2 4 Miles
Data Sources:PA DEPU.S. EPA BASINS
Observed Nitrate vs. Distance from Mouth
(Wissahickon Creek)
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
9 10 11 12 13 14 15 16 17 18 19 20 21
Distance from Mouth of Wissahickon Creek (miles)
Co
nc
en
tra
tio
n(m
g/L
)
Ambler WWTP
Thompson Dam
Gross Dam
Up
pe
rG
ywn
ed
dW
WT
P
No
rth
Wa
les
WW
TP
Observed Nitrate vs. Distance from Mouth
(Wissahickon Creek)
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
9 10 11 12 13 14 15 16 17 18 19 20 21
Distance from Mouth of Wissahickon Creek (miles)
Co
nc
en
tra
tio
n(m
g/L
)
Ambler WWTP
Thompson Dam
Gross Dam
Up
pe
rG
ywn
ed
dW
WT
P
No
rth
Wa
les
WW
TP
• Occurs under low flow
conditions
• For example :
Nutrient Impairment –
Low DO
Steady State Example
Cumulative Condition
Impairment results under specific conditions(climatic)
Same inflows may not create an immediateresponse
Fraction of loading inflows may accumulate inthe system and became a source under certaincondition
Impairment may results from long-term loadingaccumulation
23
Lake or Estuary
Loadings accumulateand cause delayed effect
All sources contribute
Cumulative ExampleLake Tahoe
Episodic Condition
Impairment occurrence varies rapidly with time
Impairment may follow a random process
accidental release/spills/bypass
wet-weather and rainstorm dependent
Stormwater, Combined Sewer Overflows, SanitarySewer Overflows are also key sources
Atmospheric Deposition
Nonpoint sources may be a major contributors
24
Wet Weather ExampleFecal Coliform (Muddy Creek)
0
5,000
10,000
15,000
20,000
25,000
30,000
Jun-94 Sep-94 Jan-95 Apr-95 Jul-95 Oct-95 Feb-96 May-96 Aug-96
Fe
ca
lC
olifo
rmCo
nce
ntr
ati
on
(#
/1
00
ml)
Obs WQ Modeled WQ
Waterbody Response Categories
SteadyState
Cumulative Episodic
River/Stream
I II III
Lakes/Reservoir
IV
Estuaries VI
V
25
Conceptual Models…
Simplified TPChlorophyll-a
Detailed
Model SelectionCriteria DefinedModel SelectionCriteria Defined
WQTargets
ConceptualModel
ManagementOptions
DataInventory
Preferred ModelsSelected
Preferred ModelsSelected
Review and EvaluationReview and Evaluation
DP
DP
Spatial/Temporal Scales of TargetsAvailable data (inputs/calibration)
Physical/Chemical/BiologicalProcesses
Implementation Recommendations
Available Models/ResourceNeeds Assessment
Available Models/ResourceNeeds Assessment
• Process/ConstituentRepresentation
• Spatial/Temporal Capabilities• Model Resource Needs• MSD Computational
Resources/Preferences
Model ResourceNeeds
Model ResourceNeeds
DP
Model Applicationand Configuration
Plan
Model Applicationand Configuration
Plan
Model/Methods Selection Inputs
DPDecisionPoint
26
Palo Verde Outfall Drain, CABacteria TMDL
Agricultural irrigation supply canal system
Flow controlled by a Colorado Riverdiversion
Minimal flow and bacteria monitoring data
Arid region – dry flow considered critical
Range of nonpoint and point sources
Palo Verde Outfall Drain Modeling Approach
Performed detailed source analysis and identified septic systems andwildlife as major contributors
Developed a mass-balance spreadsheet model Represented main stem with tributary inputs
Series of plug-flow reactors
Used channel geometry, flow estimates, and bacteria observations
Predicted the change in bacteria concentration for E.coli, fecal coliform bacteria,and enterococcus throughout the main-stem
27
Palo Verde Outfall Drain Model
Completed model and TMDLdevelopment in less than 4months
Provides a flexible basis for theRegional Board to evaluatebacteria source-responsescenarios
Wissahickon CreekWatershed
• Drains approximately 64 sq.miles (41,000 acres)
• Approximately 24.1 mileslong
• Dominant land uses includeindustrial, residential,agricultural, undevelopedwoodlots, and recreational
• Impaired due to sedimentand nutrients
Willow Run - West
Prophecy Creek
Wises Mill Trib.
Valley Rd. Trib.Monoshone Creek
Creshiem Creek
Paper Mill Run
Sandy Run
Pine Run
Rose Valley Trib.
Willow Run - East
Trewellyn Creek
Lorraine Run
MONTGOMERY CO.
PHILADELPHIA CO.County BoundariesWissahickon WatershedReach File, V3
Wissahickon Creek
N
2 0 2 4 Miles
Data Sources:PA DEPU.S. EPA BASINS
28
Willow Run - West
Prophecy Creek
Wises Mill Trib.
Valley Rd. Trib.Monoshone Creek
Creshiem Creek
Paper Mill Run
Sandy Run
Pine Run
Rose Valley Trib.
Willow Run - East
Trewellyn Creek
Lorraine Run
MONTGOMERY CO.
PHILADELPHIA CO.County Boundaries
Wissahickon WatershedReach File, V3303(d) Listed Segments: Nutrients
Wissahickon Creek
N
2 0 2 4 Miles
Data Sources:PA DEPU.S. EPA BASINS
Nutrient TMDLObjectives
Reduce reoccurrence ofDO violations
Reduce nuisance algalgrowth (periphyton)
Nutrient TMDLAnalytical Framework
Steady state model for simulation of critical conditions (lowflow) EFDC hydrodynamic model
Modified version of WASP to simulate periphyton growth processes
Processes linking nutrients and DO Periphyton growth processes
Considered additional impacts on DO due to SOD
Nonpoint sources on a case-by-case basis (e.g., golf courses,sediments behind dams)
Focus attention on point sources
29
Nutrient TMDLModel Development
Model Calibration Hydrodynamic model (EFDC) calibrated to “time-of-travel” study
Water quality model (WASP) calibrated to instream water quality data and periphytondata
Model Configuration of Critical Conditions Modeling system configured to critical conditions
7Q10 background flows
Discharge design flows
Target based on instream DO criteria for Trout Stocking and Warm Water Fishes
WLAs developed for NH3-N, NO3+NO2-N, ortho PO4-P, and CBOD5
Nutrient TMDL - Calibration to PeriphytonBiomass
0
100
200
300
400
500
0 20 40 60 80 100 120
Segment Number
Pe
rip
hy
ton
(mg
/m2
Ch
la)
Model result Survey Data
30
Nutrient TMDLCalibration
0
2
4
6
8
10
12
14
16
18
0 5,000 10,000 15,000 20,000 25,000 30,000 35,000
Distance From Mouth (m)
DO
(mg
/L)
Observed DO w ith Range Model Mean DOModel MaximumDO Model MinimumDO
Sandy Run enters
Ambler Discharge Upper Gw ynedd Discharge
North Wales Discharge
0
2
4
6
8
10
12
0 5,000 10,000 15,000 20,000 25,000 30,000 35,000
Distance From Mouth (m)
PO
4(m
g/L
)
Observed PO4 w ith Range Model Mean PO4
Sandy Run entersAmbler Discharge Upper Gw ynedd Discharge
North Wales Discharge
Nutrient TMDL - Load Reductions
WLAs reported fortwo effluent DOscenarios
Reductions relaxedwith increase in DO
CBOD5 NH3-N NO3+NO2-N Ortho PO4
North Wales Boro PA0022586 90.0 88.0 20.0 90.0
Upper Gwynedd Township PA0023256 89.0 80.0 15.1 88.0Ambler Boro PA0026603 26.0 35.3 0.0 58.3
Abington Township PA0026867 88.0 70.0 34.0 77.0Upper Dublin Township PA0029441 75.0 70.0 10.1 80.0
A - Calculated from NPDES permit limitB - Calculated from average of summer 2002 monitoring
TMDL Percent ReductionName NPDES
Major Dischargers’ Effluent DO at 6.0 mg/L
CBOD5 NH3-N NO3+NO2-N Ortho PO4
North Wales Boro PA0022586 60.0 58.0 10.0 60.0
Upper Gwynedd Township PA0023256 72.0 65.0 15.1 70.0
Ambler Boro PA0026603 14.0 10.0 0.0 58.3
Abington Township PA0026867 71.0 65.0 10.0 70.0
Upper Dublin Township PA0029441 57.9 40.0 10.1 40.1
A - Calculated from NPDES permit limitB - Calculated from average of summer 2002 monitoring
Name NPDESTMDL Percent Reduction
Major Dischargers’ Effluent DO at 7.0 mg/L
31
Siltation TMDLObjectives
Impairments due tosiltation
Sources: Urban runoff/storm
sewers
Habitat modification
No water quality criteriaavailable for siltation
Willow Run - West
Prophecy Creek
Wises Mill Trib.
Valley Rd. Trib.Monoshone Creek
Creshiem Creek
Paper Mill Run
Sandy Run
Pine Run
Rose Valley Trib.
Willow Run - East
Trewellyn Creek
Lorraine Run
#
Wissahickon Creek
Wissahickon WatershedReach File, V3303(d) Listed Segments: Siltation
N
2 0 2 4 Miles
Data Sources:PA DEPU.S. EPA BASINS
Endpoint
Reference Watershed approach
No numeric instream criteria for siltation in PA
Reference watershed used to set endpoints for TMDL development
AVGWLF model developed for both the Wissahickon Creek andreference watersheds for comparison of siltation loads Overland load form storm runoff
Streambank erosion
Siltation TMDLAnalytical Framework
32
Goal: Identify similar, unimpaired watersheds to be used todevelop siltation TMDL endpoints.
Data used:
Ecoregion coverages Land use distribution
Topography Watershed size
Soils Point source inventory
Surface Geology
Siltation TMDLReference Watershed Selection
Siltation TMDL
WISSAHICKONCREEK
IRONWORKSCREEK
MontgomeryCounty
BucksCounty
PhiladelphiaCounty
0 6 12 Miles
N
EW
S
Ironworks Creek
Wissahickon
Streams reaches
County Boundaries
3 miles
ReferenceWatershed –
Ironworks Creek
33
Siltation TMDL
Good match betweenmost categories thatimpact siltation Landuse is key
Soils and ecoregion alsocritical
Point sources areinsignificant loads
Difference in watershedsize could be addressed inmodel approach
Stream
Wissahickon
Creek
Ironworks
CreekWatershed Type Impaired Watershed Reference Watershed
Watershed Size (acres) 40,928 11,114Geologic Province Piedmont Piedmont
Dominant Rock Types
Sandstone/ Metamorphic-
Igneous/ Shale/
Carbonate
Sandstone/
Metamorphic-Igneous
Dominant Soils C & B C & B
Ecoregions
Triassic Lowlands
Piedmont Uplands
Piedmont Limestone
Dolomite Lowlands
Triassic Lowlands
Piedmont Uplands
Percent Slope of
Watershed 0.25% 0.63%Point Sources 14 0Percent Urban 43% 44%Percent Forested 40% 31%Landuse Types: % Landuse % Landuse
Low Intensity Development 34.10% 39.80%High Intensity Development 8.50% 4.20%Hay/Pasture 7.10% 11.70%Cropland 8.90% 10.90%Conifer Forest 2.40% 1.80%Mixed Forest 10.20% 10.30%Deciduous Forest 28.00% 19.60%Quarry 0.30% 0.00%Coal Mine 0.02% 0.00%Transitional 0.40% 0.10%
Comparison ofWissahickon Creek toIronworks Creek
Siltation TMDL - Hydrology Calibration
Monthly hydrologycalibrationperformed on boththe Wissahickonand referencewatersheds
0.00
5.00
10.00
15.00
20.00
25.00
Ap
r-9
3
Ju
n-9
3
Se
p-9
3
De
c-9
3
Ma
r-9
4
Ju
n-9
4
Se
p-9
4
De
c-9
4
Ma
r-9
5
Ju
n-9
5
Se
p-9
5
De
c-9
5
Ma
r-9
6
Ju
n-9
6
Se
p-9
6
De
c-9
6
Ma
r-9
7
Ju
n-9
7
Se
p-9
7
De
c-9
7
Ma
r-9
8
Ju
n-9
8
Se
p-9
8
De
c-9
8
Ma
r-9
9
Ma
y-9
9
Au
g-9
9
No
v-9
9
Fe
b-0
0
Ma
y-0
0
Au
g-0
0
No
v-0
0
Fe
b-0
1
Flo
w(c
m/m
on
th)
ObservedFlow
ModeledFlow
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
20.00
D J F M A M J J A S O N D J F M A M J J A S O N D J F
Flo
w(c
m/m
on
th)
Observed Flow
Modeled Flow
34
Siltation TMDL - Water Quality Calibration
Calibration less of issue due to empirical aspect of model
“Validation” of model using water quality data at mouth of WissahickonCreek
Validation limited due to limited water quality data for storm flows
Monthly sediment loads validated
0
100
200
300
400
500
600
700
800
J-94 J-94 J-95 J-95 J-96 J-96 J-97 J-97 J-98 J-98 J-99 J-99 J-00
Sedim
entY
ield
(Mg/m
o)
Modeled Sediment Load Observed Sediment Yield (Mg/mo) - with 95% Confidence Interval
Siltation TMDLCalculation
Watershed was dividedinto subwatersheds foreach 303(d) listed streamsegment
TMDLs were calculatedfor each stream segment
TMDL components: LAs to upstream loads
WLAs to dischargers andstormwater permits (MS4s)
10% margin of safety
35
Siltation TMDLMS4 Permits
MS4s requiredWLAs
Each municipalityholds its own MS4permit
WLAs include: Overland load from
runoff
Streambankerosion
PHILADELPHIA
HORSHAM
ADNOR
LOWER MERION
ABINGTO
WHITPAIN
ION
WHITEMARSH
UPPER DUBLIN
WARMINSTER
CHELTENHAM
LOWER GWYNEDD
UPPER GWYNEDD
UPPER MORELAND
ORRITON
LANSDALE
RISTOWN
HATBORO
AMBLER
CONSHOHOCKEN
DGEPORT
JENKINTOWN
IVYL
NORTH WALES
WEST CONSHOHOCKEN
SPRINGFIELD
PLYMOUTH
MONTGOMERY
Data Sources:PA DEPU.S. EPA BASINSPASDA
Lake Elsinore Eutrophication
36
Lake Elsinore Eutrophication
Lake Elsinore
5 0 5 Miles
LakesStreams (RF3)San Jacinto Watershed
Watershed Model(LSPC)
ReceivingWater Model
(EFDC)
ReceivingWater Model(BATHTUB)
Model Representation
Linkage to separatereceiving water modelsfor assessment ofmagnitude andfrequency ofimpairment
37
Which landuse category/breakdown should beconsidered? (Level of effort and detail)
• PredominantLanduse
• Type of Impacts• Future Land Use
Conversion• Data Availability• Resources
Factors to Consider
AndersonLevel 1
AndersonLevel 2
Lumped Distributed
Spatial Scale: Watershed Model
Need to define a suitable level of segmentation
Factors to Consider
Watershed• Land Use distribution• Soils• Topo/weather station
location• Data (weather, PS)
Management• Planning• Regulatory• Impact• Alternative analysis
2 Segments 8 Segments
Spatial Scale: Watershed Model
Lumped Distributed
38
Considerations for Watershed Model Configuration –Hydrologic Soil Groups
Representation of Rainfall Based on Observed Data
39
Considerations for Watershed Model Configuration –Monitoring Stations
##
#
###
#
#
#
#
##
#
#
#
##
#
#
# #
839
#
841
#
714
#
712
#
357
#
324
#
827
#
834
#
745
#
790
#
840
#
759
#
325
#
741
#
838
#
835
#
837
#
836
#
318
#
792
5 0 5 10 Miles
Streams (RF3)San Jacinto Watershed
# Stream Water Quality Stations
San Jacinto WatershedStream Water Quality Stations
Sub-Watershed Delineation and Model Representation
40
Load estimates basedon assumptions forper capita load,nutrientconcentrations, andfailure rates ofsystems.
Loading representeddynamically in LSPCmodel and driven byrainfall
Representing Septic Loads
0
100
200
300
400
500
600
700
800
10/1/1996 4/1/1997 10/1/1997 4/1/1998 10/1/1998 4/1/1999 10/1/1999 4/1/2000 10/1/2000 4/1/2001
Date
Flo
w(c
fs)
0
1
2
3
4
5
6
7
8
9
10
Daily
Rain
fall
(in)
Avg Monthly Rainfall (in) Avg Observed Flow (10/1/1996 to 6/30/2001 ) Avg Modeled Flow (Same Period)
San Jacintoheadwaters(forested)
LSPC Simulated Flow Observed Flow Gage
REACH OUTFLOW FROM SUBBASIN 33 USGS 11069500 San Jacinto River Near San Jacinto
4.75-Year Analysis Period: 10/1/1996 - 6/30/2001 Riverside County, California
Flow volumes are (inches/year) for upstream drainage area
Total Simulated In-stream Flow: 11.39 Total Observed In-stream Flow: 11.16
Total of simulated highest 10% flows: 9.52 Total of Observed highest 10% flows: 9.56
Total of Simulated lowest 50% flows: 0.00 Total of Observed Lowest 50% flows: 0.01
Simulated Summer Flow Volume ( months 7-9): 0.03 Observed Summer Flow Volume (7-9): 0.16
Simulated Fall Flow Volume (months 10-12): 0.35 Observed Fall Flow Volume (10-12): 0.41
Simulated Winter Flow Volume (months 1-3): 7.58 Observed Winter Flow Volume (1-3): 5.10
Simulated Spring Flow Volume (months 4-6): 3.44 Observed Spring Flow Volume (4-6): 5.49
Errors (Simulated-Observed) Current Run (n) Recommended Criteria
Error in total volume: 2.04 10
Error in 10% highest flows: -0.40 15
Hydrology Calibration
41
Water Quality Calibration – Mixed Land Use
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
1/1
/01
1/8
/01
1/1
5/0
1
1/2
2/0
1
1/2
9/0
1
2/5
/01
2/1
2/0
1
2/1
9/0
1
2/2
6/0
1
3/5
/01
3/1
2/0
1
3/1
9/0
1
3/2
6/0
1
4/2
/01
4/9
/01
4/1
6/0
1
4/2
3/0
1
4/3
0/0
1
5/7
/01
5/1
4/0
1
5/2
1/0
1
5/2
8/0
1
6/4
/01
6/1
1/0
1
6/1
8/0
1
6/2
5/0
1
Date
TN
(mg
/L)
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Mo
de
lF
low
(cfs
)
Observed TN Model TN "Flow"
0
0.5
1
1.5
2
2.5
1/1
/01
1/6
/01
1/1
1/0
1
1/1
6/0
1
1/2
1/0
1
1/2
6/0
1
1/3
1/0
1
2/5
/01
2/1
0/0
1
2/1
5/0
1
2/2
0/0
1
2/2
5/0
1
3/2
/01
3/7
/01
3/1
2/0
1
3/1
7/0
1
3/2
2/0
1
3/2
7/0
1
4/1
/01
4/6
/01
4/1
1/0
1
4/1
6/0
1
4/2
1/0
1
4/2
6/0
1
5/1
/01
5/6
/01
5/1
1/0
1
5/1
6/0
1
5/2
1/0
1
5/2
6/0
1
5/3
1/0
1
6/5
/01
6/1
0/0
1
6/1
5/0
1
6/2
0/0
1
6/2
5/0
1
Date
TP
(mg
/L)
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Mo
de
lFlo
w(c
fs)
Observed TP Model TP "Flow"
Interpretation of Model Results
1998TotalNitrogenLoads (WetYear)
Total Nitrogen
Zone 986,076 lbs
Total Nitrogen
Zone 8178,149 lbs
Total Nitrogen
Zone 6112,173 lbs
Total Nitrogen
Zone 573,047 lbs
Total Nitrogen
Zone 7107,217 lbs
Total Nitrogen
Zone 435,710 lbs
Total Nitrogen
Zone 355,493 lbs
To t a l Ni t r o g e nCropland
Dairy/Livestock
Forest
Urban
High-Density Residential
Medium-Density Residential
Low-Density Residential
Mobile Home/Trailor Park
Open
Orchard/Vineyards
Pasture
Septics
Total Nitrogen
Canyon Lake287,720 lbs
ManagementStrategiesIdentified for EachSource/ Landuse Urban Hydraulic/
riparianmodifications
Agricultural Other (e.g.,
pollutant tradingstudies,continuedmonitoring)
42
Supporting Planning Efforts
Lake Elsinore and CanyonLake Nutrient SourceAssessment Stakeholder led Supported RWQCB TMDL
development
San Jacinto NutrientManagement Plan Options for load reductions
(land use based)
IRWMP Specific projects identified
Septic Mgt. Plan
Los Penasquitos Lagoon - 1985
84
43
Los Penasquitos Lagoon - 2009
85
Los Penasquitos Watershed – 1970s
86
44
Los Penasquitos Watershed - Existing Land Use
87
Model Development
1405
1412
1403
14091406
1408
1407
1410
1411
1404
1402
1401
0 1 20.5
Mi les
0 3 61.5
Kilometers
NAD_1927_StatePlane_California_V_FIPS_0405_feetMap produced 11-06-2009
Los Peñasquitos Watershed Model Catchments
Map extent
Poway
San Diego
Del Mar
Pacific Ocean
San Diego
Riverside
Los Angeles
Orange
Legend
Catchments
Watershed Outline
NHD stream
NHD Waterbody
EFDC Model of Lagoon LSPC Model of Watershed
45
Watershed Model Calibration/Validation
y = 1.111x + 1.4645
R2
= 0.9939
0
20
40
60
80
100
0 20 40 60 80 100
Average Observed Flow (cfs)
Ave
rage
Mod
ele
dF
low
(cfs
)
Avg Flow (1/1/1993 to 1/31/2000)
Line of Equal ValueBest-Fit Line
J F M A M J J A S O N D
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9 10 11 12
MonthF
low
(cfs
)
0
0.5
1
1.5
2
2.5
3
Mo
nth
lyR
ain
fall
(in
)
Avg Monthly Rainfall (in)
Avg Observed Flow (1/1/1993 to 1/31/2000)Avg Modeled Flow (Same Period)
y = 0.9454x - 0.9344
R2
= 0.9856
0
10
20
30
40
50
0 10 20 30 40 50
Average Observed Flow (cfs)
Ave
rag
eM
od
ele
dF
low
(cfs
)
Avg Flow (1/1/2000 to 2/28/2008)
Line of Equal ValueBest-Fit Line
J F M A M J J A S O N D
0
10
20
30
40
50
1 2 3 4 5 6 7 8 9 10 11 12
Month
Flo
w(c
fs)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Mo
nth
lyR
ain
fall
(in
)
Avg Monthly Rainfall (in)
Avg Observed Flow (1/1/2000 to 2/28/2008)Avg Modeled Flow (Same Period)
Watershed Model Calibration/Validation
0
50
100
150
200
250
11/30 0:00 11/30 12:00 12/1 0:00 12/1 12:00 12/2 0:00
TS
S(m
g/L
)
Model
Measured
0
50
100
150
200
250
12/7 0:00 12/7 12:00 12/8 0:00 12/8 12:00
TS
S(m
g/L
)
0
50
100
150
200
250
2/3 0:00 2/3 12:00 2/4 0:00 2/4 12:00
TS
S(m
g/L
)
46
Lagoon Model Salinity Calibration
How is the Model Used?
Key decisions: No numeric target for
sediment/siltation Establishing link
between watershedloading and lagoonsedimentation
Variables Watershed loading Lagoon flushing Lagoon vegetation
47
Establishing a Target
Document historical changes in lagoon condition
Research available literature
Identify unimpaired time period
Correlate with land use changes over time
TMDL numeric target based on unimpaired time period
Estimate watershed sediment contribution (from historic landuse)
Calculate total based on watershed model output
93
Decision
LSPC modeled watershed loads:
1975 land use (assumed unimpaired conditions inlagooon)
2009 land use
Requires 70% watershed load reduction
94
Note the lagoon model wasn’t needed!
48
Questions