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

1. Watershed Monitoring and Modeling in Switzer, Chollas, and Paleta Creek Watersheds Kenneth Schiff Southern California Coastal Water Research Project www.sccwrp.org

2. 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

3. 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

4. Road Map • Source question • Fate and transport • Prioritization

5. 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

6. 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?

7. 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

8. 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

9. Modeled Land Uses • High density residential • Low density residential • Industrial • Commercial • Agricultural • Open

10. 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

11. Insert maps….

13. 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?

14. 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

15. 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

16. Road Map • Source question • Fate and transport • Prioritization

17. 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

18. 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

19. Data Collection Strategy for Physical Parameters • Have creek mouth geometry • Do we have bathymetry? • Have substrate information

20. 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

21. 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

22. 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?

23. Summarizing