Identifying Stressors, Sources, and Needed Pollutant Load ... · Identifying Stressors, Sources,...

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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

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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

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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


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


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

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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?

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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

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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)

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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

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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.


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


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

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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

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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

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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

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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

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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.


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


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Willow Run - West

Prophecy Creek

Wises Mill Trib.


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


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

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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.


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


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

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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 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 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

Identifying Stressors, Sources, and Needed Pollutant Load ... · Identifying Stressors, Sources,...

Documents

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