Watershed Monitoring and Modeling in Switzer, Chollas, and Paleta Creek Watersheds

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Watershed Monitoring and Modeling in Switzer,
Chollas, and Paleta Creek Watersheds

• Kenneth Schiff
• Southern California Coastal Water Research
  Project
• www.sccwrp.org

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By The End Of Today

• Review approach to sampling designs
• Basic agreements on most important elements
• Opportunities for collaboration?
• Achieve sufficient detail for SCCWRP to write a
  workplan

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Agreements From Our last Meeting

• Sediments at the mouth of several urban creeks
  draining to SD Bay are listed as impaired
• - chemistry, toxicity, benthic community
• Two questions for the next phase
• What are the loads of CPOCs to the creek mouth?
• How much of the total load deposits in the creek
  mouth?
• Several CPOCs
• Chlordane, PAHs, PCBs, Cu, Pb, Zn,
• As, Hg

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Road Map

• Source question
• Fate and transport
• Prioritization

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Sources

• Chollas Creek watershed
• - Paleta and Switzer Creek watersheds
• Runoff directly to the Chollas Creek mouth
• Navy, NASSCO
• Atmospheric deposition to the creek mouth
• Deposition on the watershed and on the Bay
• San Diego Bay
• - tidal inputs

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Watershed Inputs

• Break into two parts
• Use combination of empirical data and wet weather
  modeling
• TSS, metals, PAHs
• Can we predict changes in loads and
  concentrations?
• Use empirical data
• Chlorinated hydrocarbons
• Can we detect loads or concentrations?

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Approach to Building a Watershed Model

• Physical data for the model domain
• - watershed delineation, stream properties, land
  use, etc.
• Calibrate flow and water quality at small
  homogeneous land uses
• Validate flow and water quality at the end of the
  watershed
• - cumulative of all land uses

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Data Collection Strategy for Wet Weather

• Physical data largely available
• Use previously collected data for land use
  information
• - requires certain assumptions
• Collect validation data at the end of each
  watershed
• requires local data for validation
• Historical data is valuable
• Dynamic models necessitates dynamic water quality
  information
• - requires multiple samples across the hydrograph

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Modeled Land Uses

• High density residential
• Low density residential
• Industrial
• Commercial
• Agricultural
• Open

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Sampling Design for Wet Weather

• Four sites
• - North and South Fork Chollas, Switzer, Paleta
• Three storms each
• - continuous flow data
• Pollutograph for model validation
• 10 to 12 samples per site event
• TSS, metals, and PAH
• Flow weighted composites for non-modeled
  components
• - large volume samples for low detection limits

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Insert maps.
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Direct Runoff To The Creek Mouth

• Similar strategy for Navy and NASSCO as for
  Chollas Creek
• Combination of empirical data and wet weather
  modeling
• Two choices for TSS, metals, PAHs
• Rely on existing monitoring data
• Collect additional data to support model
• Use empirical data
• Can we detect any chlorinated hydrocarbons?

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Sampling Design for Atmospheric Deposition

• Focus will be deposition onto the water surface
  of creek mouth
• - Supplement with samplers in the watershed as an
  option
• One site as close to creek mouth as possible
• Minimum of 12 sample events
• Use surrogate surfaces for metals
• Supplement with atmospheric concentrations for
  confirmation
• Use high volume samplers for organics
• Supplement with water samples for diffusion
  estimates

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Sampling Design for Bay Inputs

• Two options
• Use existing data of bay water quality
• Assume tidal forcing
• Collection of site specific data
• Bay water quality at the boundary condition on
  incoming and outgoing tides
• Supplement with velocity measurements if desired

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Road Map

• Source question
• Fate and transport
• Prioritization

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Simple Elements of An Estuary Model

• Wet weather
• Stormwater plume growth and dissipation
• Dry weather
• Secondary mixing with tides and tugs
• Particle (and associated CPOCs) dynamics
• Settling
• Diffusion

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Approach To Building An Estuary Model For Wet
Weather

• Physical data
• Geometry, bathymetry, substrate
• Calibration data
• Hydrodynamic, particle, water quality, sediment
  quality data
• Validation data
• Predict measured conditions based on calibration
  exercise

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Data Collection Strategy for Physical Parameters

• Have creek mouth geometry
• Do we have bathymetry?
• Have substrate information

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Data Collection Strategy for Hydrodynamics

• Watershed and tidal forcing
• Surface elevation
• Optional velocity information
• Stormwater plume dynamics
• Horizontal and vertical profiles of salinity,
  temp, turbidity
• Calibration and validation data sets
• Multiple storm events

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Data Collection Strategy for Particle and Water
Quality

• Particles and water quality in the discharge
• Particle size information
• Stormwater plume dynamics
• Particle size and water quality
• Optional sediment traps
• Calibration and validation data sets
• Multiple storm events

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Special Studies

• Secondary mixing
• Dye studies
• Tug resuspension
• Partition coefficients
• Dissolved and particulate phases in water column
  and in sediments
• Acid volatile sulfides in sediments
• Other?

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Summarizing