1. EPA HWI Comments on CA Assessment June 26, 2013 HSP Call 2 major categories of comments: – Report writing (we will work on this) – Content/Analysis/Discussion (today’s discussion) NHD+ v. 2 (2012) Watershed Condition – Component metrics Stream Health – Component metrics Watershed Vulnerability – Component metrics

2. NHDPlus Catchments V.1 (2005) 135,255 total catchments Delineated using 1:100,000 medium scale stream network resolution

4. Relative Watershed Structural Integrity

5. Watershed Structural Integrity 3 Types of Indicators Natural % Natural Land Cover % Intact Active River Area Anthropogenic Modification % Artificial Drainage Area Road Crossing Density Dam Storage Ratio Risk Soil Infiltration Capacity (runoff risk) Sediment Risk Relative Watershed Structural Integrity

6. Watershed Structural Integrity 3 Types of Indicators Natural % Natural Land Cover % Intact Active River Area Anthropogenic Modification % Artificial Drainage Area Road Crossing Density Dam Storage Ratio Risk Soil Infiltration Capacity (runoff risk) Sediment Risk ACTUAL CONDITION POTENTIAL CONDITION ACTUAL CONDITION Relative Watershed Structural Integrity

7. Watershed Structural Integrity 3 Types of Indicators Natural % Natural Land Cover % Intact Active River Area Anthropogenic Modification % Artificial Drainage Area Road Crossing Density Dam Storage Ratio Risk Soil Infiltration Capacity (runoff risk) Sediment Risk ACTUAL CONDITION POTENTIAL CONDITION ACTUAL CONDITION Relative Watershed Structural Integrity

8. Numerical Distribution?

9. Conductivity Nitrate Physical Habitat MMI California Rapid Assessment Method Score Temperature Turbidity California Stream Condition Index pH Large Flood Flow Alteration Small Flood Frequency Alteration Alt. in Fall Rate after High Flows Small Flood Duration Alt. Small Flood Date Alt.

10. Conductivity Nitrate Physical Habitat MMI California Rapid Assessment Method Score Temperature Turbidity California Stream Condition Index pH Large Flood Flow Alteration Small Flood Frequency Alteration Alt. in Fall Rate after High Flows Small Flood Duration Alt. Small Flood Date Alt. 11 2 2 3 3

11. Conductivity0.88 Nitrate0.83 Physical Habitat MMI0.83 California Rapid Assessment Method Score0.80 Temperature0.66 Turbidity0.66 California Stream Condition Index0.63 pH0.38 Large Flood Flow Alteration0.69 Small Flood Frequency Alteration0.67 Alt. in Fall Rate after High Flows0.62 Small Flood Duration Alt.0.59 Small Flood Date Alt.0.57 Decreasing Model Performance 11 2 2 3 3

12. 0.80 0.83 High Correlation Statistics

13. Moderate Correlation Statistic 0.63

15. Water Quality Indicator Cross-Validation Correlation Statistic Water Temperature0.66 pH0.38 Conductivity0.88 Turbidity0.66 Nitrate0.83 KEEP Conductivity: good integrator of watershed stress (measure of all ions in the water). Little to no temporal variability. Nitrate: good indicator of anthropogenic modification in catchments (ag, urbanization). Minimal temporal variability. DROP pH: poor correlation stats. Getting an accurate pH reading can be analytically challenging (improper / infrequent calibration, poor probe maintenance, etc.) Temp: temporally variable (diurnal, seasonal); spatially variable (elevation, latitude) Turbidity: temporally variable with respect to antecedent storm condition

16. Hydrologic Condition Indicator Probability of Correctly Classifying a Site as Altered/Unaltered Large Flood Flow Alteration0.69 Small Flood Duration Alteration0.59 Small Flood Date Alteration0.57 Small Flood Frequency Alteration0.67 Alteration in Rate of Fall after High Flow Pulses 0.62 Hydrologic Condition Currently doesn’t incorporate water use Water use (not withdrawals) is available at the county level, but has been estimated for the catchment scale for incorporation into water use vulnerability (see page 105). Consider decreasing its weight in the Stream Health Index

18. Land Use Vulnerability Projected Change in Impervious Fire Regime Condition Class

19. Projected Impervious Surface Change Changes in impervious are predicted to be either very LOW or very HIGH, but nothing in between. This binary-like distribution of the data may not be particularly informative for the vulnerability assessments