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CDFG SJR Fall-run Chinook Salmon Model CWEMF November 4, 2005

CDFG SJR Fall-run Chinook Salmon Model CWEMF November 4, 2005. Objectives. Brief Overview of Model Development Describe Model Structure Describe Model Calibration/Validation Describe Model Scenarios. Overview. San Joaquin River Salmon Production as a function of Spring Vernalis Flow.

Samuel
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CDFG SJR Fall-run Chinook Salmon Model CWEMF November 4, 2005

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  1. CDFGSJR Fall-run Chinook Salmon ModelCWEMF November 4, 2005

  2. Objectives • Brief Overview of Model Development • Describe Model Structure • Describe Model Calibration/Validation • Describe Model Scenarios

  3. Overview San Joaquin River Salmon Production as a function of Spring Vernalis Flow

  4. Study Area Courtesy of USFWS

  5. Salmon Life History

  6. Salmon Cohort“Singe Year Production Indicator” Brood Year Production Juvenile Age 1 Age 5 Age 2 Age 4 Age 3 CWT Recovery Scale Analysis

  7. Salmon Escapement“Multi-Year Production Indicator” Age 1 Year 1 Annual Carcass “Creamer” Survey Age 2 Year 2 Age 3 Year 3 Age 4 Year 4 Age 5 Year 5

  8. 1995 WQCP Triennial Review • CDFG Challenge: • Are the Flow Objectives Working? • What is the status of the salmon population? • What fraction of juvenile salmon are receiving protection? • What is the status of the VAMP experiment?

  9. 1983-1995 Average 42,285 1996-2004 Average 35,004 SJ Basin Production Year Populations Are Declining

  10. Level of Protection

  11. VAMP Implementation • VAMP: • Lock Down Uncertainty at Extremes First • Since 2000: • Result: • Continued uncertainty • Need several successive high flow range tests to define/solidify relationship

  12. More Flow = More Salmon

  13. 2005 SWRCB ’95 WQCP Review • CDFG: • presented its concerns • asked for peer review • SWRCB: • peer reviewed already occurred • CDFG: develop flow recommendations

  14. Chalkboard E = mc? What +/- What = More Salmon? Harvest? Exports? Disease? Predation? Flow? Gravel?

  15. Model Logic • Delta Exports • weak correlation to cohort production

  16. Model Logic • Ocean Harvest • weak correlation to cohort production Harvest - Sacramento, San Joaquin and CVI Ocean Harvest versus Tuolumne Escapement

  17. Mossdale Smolts Previous Year Escapement Model Logic • Adult Stock Density Limitations Ricker Stock-recruit relationship (density dependent mortality governor) appears questionable More females = more juveniles (Tuolumne River)

  18. Adult Stock Density Limitations Density Dependent Governor ? Higher Escapement Higher Spring Flow Higher Cohort Production Higher Escapement Lower Spring Flow Lower Cohort Production Multiple Regression 1973-1999 R-square = 0.75 P = .001 Tuolumne River data

  19. Model Logic • Instream Flow Strong correlation to cohort production in relation to spring flow SJB east-side tributaries principle flow & salmon contributor

  20. Flow Features • Increased Vernalis Flow Magnitude/Duration/Frequency all projected increased adult salmon production

  21. Now What? • Challenge: “How to link salmon life history production to flow magnitude & duration?” • Solution: “Develop a tool”

  22. Model Concept • Flow primary driving factor in population (not harvest, exports or adult stock density) • Quantify relationships between: • flow and juvenile production • flow and juvenile survival • juvenile survival and adult escapement • Simulate production over time

  23. Eureka! The Light Bulbs Went On!

  24. Model Features • Excel spreadsheet platform • Links life history stages by numerical production at each phase • Predicts adult escapement (1967-2000) • Flow duration & magnitude variable • Predicts escapement change & water volume • Has 95% confidence level predictions • Customizable input parameters

  25. Model Refinements • Limits predictions to data set • Uses San Joaquin Basin data for age cohort reconstruction • Smolt Outmigration pattern WY Type specific • Allows for HORB/non-HORB smolt survival • 95% confidence levels predictions

  26. Conceptual Model Vernalis Flow Mossdale Smolts Delta Survival Adult Cohort Annual Escapement (spawners) Chipps Smolts Escapement Reconstruction

  27. Vernalis Flow - Mossdale Smolts

  28. Outmigration Pattern

  29. Conceptual Model Vernalis Flow Mossdale Smolts Delta Survival Adult Cohort Annual Escapement (spawners) Chipps Smolts Escapement Reconstruction

  30. Delta Survival

  31. Conceptual Model Vernalis Flow Mossdale Smolts Delta Survival Adult Cohort Annual Escapement (spawners) Chipps Smolts Escapement Reconstruction

  32. Adults versus Outmigrants

  33. Reconstruct Adult Escapement

  34. SJR Scale vs CV CWT

  35. Repeat Cycle Combine spawners with Vernalis flow to predict Mossdale Smolt Production Vernalis Flow Mossdale Smolts Delta Survival Adult Cohort Annual Escapement (spawners) Chipps Smolts Escapement Reconstruction

  36. Model Calibration & Validation • Two Approaches • Calibrate with subset/validate with remaining • Calibrate with entire data set • Parameters • Escapement pattern • Time period average • Replacement ratio • Stay within 95% CI

  37. SJ Basin Escapement 1967-2000 -----Historic -----Modeled

  38. 95% Confidence Intervals HistoricUpper 95% CILower 95% CI

  39. Model Scenarios • Ten model runs • Four presented

  40. What Scenarios • Possible Goal Attainment Scenarios • Vary Flow with Window Constant • VAMP (3200-7000 with 31 day window) • Constant Flow & Window Constant • 10,000 all WY Types & 31 day window • Constant Flow & Variable Window • 10,000 all WY Types & Variable WY Window • Variable Flow & Variable Window • 5-20K Flow & 31-90 day Window

  41. 10 Chosen

  42. Existing Flow Magnitude

  43. D-1641 Flows (No HORB)

  44. D-1641 Flows (With HORB)

  45. Constant Flow

  46. Constant Flow

  47. Flow Varies by Water Year Type

  48. Flow varies by Water Year Type

  49. Variable Flow and Duration

  50. Variable Flow and Duration

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