CCWD: Using DSM2 Historical July20, 2006 1 Two Applications of the DSM2 Historical Model: Modeling Contaminant Spills and Using Salinity Fingerprints to

CCWD: Using DSM2 HistoricalJuly20, 2006

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Two Applications of the DSM2 Historical Model:

Modeling Contaminant Spills and Using Salinity Fingerprints to Improve DSM2

Real-Time Forecasts

Tom Rose

and

Marianne Guerin


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Background• CCWD uses Delta Water

• WQ Implications– Salinity– DOC

• Supply Issues– Direct delivery– Blending – Emergency storage

• Forecasting WQ at intakes to help Operations vital

– G-Model – zero-dimensional– DSM2 – accuracy variable at

intakes – time-consuming


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Talk Logistics – Using the Historical Model

• Modeling Contaminant Spills– Motivation for the work

– Methodology

– Results

– Future direction

• Improving Forecasts– Background

– Objective

– Method

– Findings

– Future work – suggestions?

• Background– CCWD Water Supply and Quality Issues

– Using DSM2 Historical Model


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Emergency Modeling: Contaminant Spills

• Motivation– Operations – needs to know what to do NOW– CCWD informed immediately, or, after the event

• Operational ?’s: When/Where/How Much/How Long– Safety of water supply

• Toxicity• Concentration

– Ability to deliver water• Arrival time at intakes• Which intakes (Old River, Rock Slough, Mallard)

– Cost• Using Los Vaqueros reservoir• Damage to pumps• Duration of shut-down


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Use Historical Model and PTM

• IDEA – For a given set of hydrological and operational conditions, find two+ times in Historical Model that ‘bound’ this hydrology– SAC Flow and DCC– SJR flow and HORB– Exports – SWP and CVP– CCWD – Old River, Rock Slough

• Use PTM to run particle tracking models for first arrival time of contaminant


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Method – ‘Quick and Dirty’

• Method:– Use prepared plots to find candidate times– Use HEC-DSSVue tables to narrow search– Run PTM at two (or more) times by injecting

particles at source• First arrival times at Old River Rock Slough – ‘flux.txt’

• Visualize for qualitative information for location of contaminant


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Hypothetical Example

Mar99 Jun99 Oct990

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Vern Flow 1999, DSM2 Simulation, Hist-200605

Vern R. Flow 1999

Head Old Riv

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Vern Flow 2000, DSM2 Simulation

Vern R. Flow 2000

Head Old Riv

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Vern R. Flow 2001

Head Old Riv

Historical 2006-05 Plots.m

17-Jul-2006 MG

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Vern R. Flow 2002

Head Old Riv

03/06/06: spill at 1:00 AM, downstream of Vernalis, ~ DSM2 node 3• SAC+SJ <83K cfs; Exports: ~6.8K cfs; No HORB or DCC


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PTM Results: spill arrives in less than two days

Hypothetical Spill

Sac SJR Sac+SJR CVP SWP CVP+SWP Old River Rock Sl3/6/2006 70331 12209 82,540 4321 2431 6752 243 12Arrival 1Day 19 hrs N/AMax % 2.8% N/A

(pulse only)DSM2 Historical

02/15/99 72,789 13,555 86,344 4323 527 4850 61 44Arrival 1Day 2145 hrs ~ 30 daysMax % 10.6% 0.1%

02/22/00 72,575 12,066 84,641 4133 8442 12575 25 7Arrival 8 days 3 hrs ~ 29 daysMax % 7.2% 0.1%

Flow measurements in CFS


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Compare Real Result and Closest Scenario

Mar 2006 Feb 1999


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Compare Two Scenarios

Feb 2000 Feb 1999Feb 2000 Feb 1999


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Next Step ?

• ‘Quick and Dirty’ – result in ~ hour– Example gave reasonable, fairly conservative

estimates– BUT, may not be able to find good ‘brackets’

• Real-time DSM2 – – fairly time-consuming – need lots of data (but not EC if just a spill)– accuracy variable – see next talk

• More work with Historical DSM2?


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• Use DSM2 salinity fingerprinting in conjunction with field data to characterize the sources of modeled salinity error at CCWD intakes in the Delta, and at selected other locations

• The Objectives are to: – Identify systematic bias (seasonal, operational, …)– Quantity the error to allow us to put error bars on

DSM2 forecasts– Possibly develop relationships to correct bias

• We’re NOT trying to calibrate the model

Using the Historical Model to Improve Forecasts


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CCWD’s Old River Intake

01/01/01 01/01/02 01/01/03 01/01/04 01/01/05 01/01/060

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1200ROLD034: Comparison of DSM2 EC Output and CCWD EC Data

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DSM2 outputCCWD data


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Method

• Compare residual (model – data) with:– Salinity fingerprints– NDOI (Net Delta Outflow Index)– DICU (Delta Island Consumptive Use)– Operations

• DCC (Delta Cross Channel)• HORB (Head of Old River Barrier)• Exports (SWP, CVP)

• Look for and characterize bias at:– Jersey (RSAN018), Holland (ROLD014), Bacon

(ROLD024), CCWD Old R. Intake (ROLD034): – Started looking at Jersey Point – easiest– Started investigating North, moved South


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EC-MTZ: Major Contributor to Jersey Point Modeled Error

Jan94 Jan95 Jan96 Jan97 Jan98 Jan99 Jan00 Jan01 Jan02 Jan03 Jan04 Jan05 Jan06

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RSAN018: Comparison of Residual EC (Model - Data) and EC-MTZ Fingerprint

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Residual (Model - Data)

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EC-MTZ Fingerprint


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Residual < 0: Occurs as Salinity is Falling in Late Fall


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RSAN018: Comparison of Negative Residual EC (Model - Data) and EC-MTZ Fingerprint

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Residual (Model - Data) (Negative Only)

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EC-MTZ Fingerprint


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Residual > 0: Occurs in Fall as Salinity is Rising ….


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RSAN018: Comparison of Positive Residual EC (Model - Data) and EC-MTZ Fingerprint

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Residual (Model - Data) (Positive Only)

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EC-MTZ Fingerprint


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JP Residual: Interesting Relationship With DICU/NDOI


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RSAN018: Comparison of Residual EC (Model - Data) and (Consumptive Use)/(NDOI)

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DICU/NDOI


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Holland Tract: EC-MTZ Relationship Evident, But Not as ‘Clean’ as JP

01/01/00 01/01/01 01/01/02 01/01/03 01/01/04 01/01/05 01/01/06-600

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EC-MTZ Fingerprint


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Bacon: Residual Changes w/EC-MTZ Are Messy (at Best), Data Questionable

01/01/02 01/01/03 01/01/04 01/01/05 01/01/06

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ROLD024: Comparison of Residual EC (Model - Data) and EC-MTZ Fingerprint

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EC-MTZ Fingerprint


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Old River Intake: Model Usually Underestimates EC, Especially In Summer and Fall as EC-MTZ Peaks

01/01/01 01/01/02 01/01/03 01/01/04 01/01/05 01/01/06-700

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EC-MTZ Fingerprint

Questionable Data


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Old River & EC-AG: Residual > 0 in Winter or Spring With Ag Events

01/01/01 01/01/02 01/01/03 01/01/04 01/01/05 01/01/06-700

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EC-AG Fingerprint

Questionable Data


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Summary of Findings• There is a suggestive relationship between modeled error and

EC-MTZ at all 4 stations investigated:– Clearest at Jersey Point– Story more complicated as move south along Old River

• Relationships w/other salinity sources and operations:– No apparent relationship with DCC or HORB operations– No apparent relationship with EC from SJR, Eastside– Not sure about EC from Ag or Sac R.

• Modeled EC at Old River:– Underestimates EC as salinity increases in late summer and fall; related

to EC-MTZ– Overestimates EC in Winter, Spring; related to EC-AG events

• Modeled EC at Jersey Point related to DICU/NDOI– Error greatest when DICU is a substantial portion of NDOI in the fall


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Future Work• More work with residuals:

– Look for relationship with export operations, including CCWD diversions

– Look at some station on Middle River– Include Volumetric Fingerprinting

• Look closer at ROLD034:– Incorporate more data– Quantify seasonal error– Look for other contributions to error

• Jersey Point:– Quantify error for EC-MTZ

Documents

CCWD: Using DSM2 Historical July20, 2006 1 Two Applications of the DSM2 Historical Model: Modeling Contaminant Spills and Using Salinity Fingerprints to