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CWWUC Presentation April 8, 2009 Application of the Integrated Impact Analysis Tool

CWWUC Presentation April 8, 2009

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CWWUC Presentation April 8, 2009. Application of the Integrated Impact Analysis Tool. Status of Division Work. Site Classes Set up Fuzzy Set Site Classes based on elevation, slope, and precipitation. 5 Site Classes High-elevation, cold water sites - PowerPoint PPT Presentation

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Page 1: CWWUC Presentation April 8, 2009

CWWUC PresentationApril 8, 2009

Application of the Integrated Impact Analysis Tool

Page 2: CWWUC Presentation April 8, 2009

Status of Division Work

Site Classes Set up Fuzzy Set Site Classes based on elevation,

slope, and precipitation. 5 Site Classes

1. High-elevation, cold water sites2. Mid-elevation, semi-cold, high gradient, drier3. Low/mid-elevation, transitional temperature, low

gradient, drier4. Low-elevation, warm water, low gradient, dry5. Mid-elevation, semi-cold, low gradient, moist

Page 3: CWWUC Presentation April 8, 2009
Page 4: CWWUC Presentation April 8, 2009

Status of Division Work

Multi-Metric Index (MMI) Based on benthic macroinvertebrates MMI score between 0 and 100 High index (Site Classes 1-3)

– Clinger Taxa– EPT Taxa– Predator/Shredder Taxa– HBI– Total Taxa

Page 5: CWWUC Presentation April 8, 2009

Status of Division Work

Low index (Site Classes 4-5)– Insect Taxa– Non-Insect Percent of Taxa– Coleoptera Percent– Predator/Shredder Taxa– Sensitive Plains Families– Clinger/Sprawler percent

Still figuring out thresholds

Page 6: CWWUC Presentation April 8, 2009

Status of Division Work

Observed over Expected Taxa (O/E) Presented some information on the Multivariate

Predictive Model that would be used to develop the Expected portion of this ratio.

April 2009 Workgroup Meeting should address this in more detail.

Basic idea – the closer the ratio is to 0, the more impaired the stream.

Page 7: CWWUC Presentation April 8, 2009

Unanswered Questions

What happens once they have the MMI and O/E? If they find that a segment (or portion of a segment) is

below the MMI threshold or the O/E is less than 1, what does that mean to a discharger?

How can a person figure out what is causing the impact to aquatic life?

Page 8: CWWUC Presentation April 8, 2009

Integrated Impact Analysis

WERF project (partly funded by EPA) to distinguish the relative impact of chemistry and habitat on aquatic life.

Teamed with GEI (Chadwick) and Risk Sciences (Tim Moore).

Has been used in Santa Ana UAA, Arid West work, and is currently being implemented by the Southeastern Wisconsin Watershed Trust.

Page 9: CWWUC Presentation April 8, 2009

Integrated Impact Analysis

Chemical Physical

Biological

++

==

Page 10: CWWUC Presentation April 8, 2009

IIA – The Gist

Uses existing statistical methods– Principle Components Analysis– All Possible Regressions– Chi-Square Automatic Interaction Detection

(CHAID) Results identify key stressors and their relative

impact. So . . . if the state identifies a stream segment or site

as impacted (through O/E or MMI), IIA can help determine what is causing that impact.

Page 11: CWWUC Presentation April 8, 2009

Basic Steps of IIA

MODEL

Apply Basic Statistics

Identify Key Stressor andResponse Variables

Rank Variables According to Relative Impact

Repeat Cycle if More Variables Are Needed

Fit Equation to Describe Interactions Between Stressors

and Response

Page 12: CWWUC Presentation April 8, 2009

Step 1Apply Basic Statistics

Perform basic descriptive statistics and develop graphics

Normalize data as needed – develop new descriptive statistics and new graphics

Compile a correlation matrix

Page 13: CWWUC Presentation April 8, 2009

Water Chemistry Basic Statistics

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Habitat Basic Statistics

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• Looking for correlations (≥0.6).

• Correlated variables can act as surrogates for each other.

Page 19: CWWUC Presentation April 8, 2009

Step 2Identify Key Stressor and Response Variables

Identify key independent stressor variables and relationships between variables using:– Principle Components Analysis (PCA) – All Possible Regressions– Chi-square Automatic Interaction Detection

(CHAID) Iterative process that systematically removes

variables from the larger pool of variables.

Page 20: CWWUC Presentation April 8, 2009

Principal Components Analysis

Useful in determining how variables relate to one another – how they move in space.

If variables generally move together, one variable can act as a surrogate for the other(s).

Page 21: CWWUC Presentation April 8, 2009

Principal Components Analysis

• Look at values with an absolute value ≥0.6.

• A component in PCA is a group of variables that move in the same direction.

• Generally, the variable with the highest score is identified as the surrogate.

• Rerun to limit number of stressors to 6 and responses to 2 or 3.

strongest

Page 22: CWWUC Presentation April 8, 2009

Principal Components Analysis

Page 23: CWWUC Presentation April 8, 2009

All Possible Regressions

Combines one response with many stressor variables into models using all combinations of the stressor variables.

Look at all combinations to see what combinations explain the greatest amount of variance with the lowest error.

Look for lowest variable count that explains the most variance.

Page 24: CWWUC Presentation April 8, 2009

All Possible Regressions

Page 25: CWWUC Presentation April 8, 2009
Page 26: CWWUC Presentation April 8, 2009

All Possible Regressions

Page 27: CWWUC Presentation April 8, 2009

Chi-Squared Automatic Interaction Detection (CHAID)

Identifies both linear and non-linear relationships between variables.

Non-parametric technique, so data should not be transformed.

Robust to missing data points.

Page 28: CWWUC Presentation April 8, 2009

NH3 range

Macroinvertebrates

P/Channel Range

Macroinvertebrates

Page 29: CWWUC Presentation April 8, 2009

Step 3Rank Variables According to Relative Impact

Develop matrix of key independent stressor variables and relationships found in Step 2

Repeat Steps 2 and 3 until the two most influential independent stressor variables are identified for each dependent response variable

Page 30: CWWUC Presentation April 8, 2009

Rank Variables According to Relative Impact

Develop a matrix of response variables and their corresponding “important” stressor variables for each of the 3 analyses.

Look for stressors identified by multiple analyses and sort by number of analyses in common.

To help with sorting, refer back to the analyses and how strong the relationships are between the stressor and response variables.

Page 31: CWWUC Presentation April 8, 2009

Matrix of Ranked Stressors for Each Response

Page 32: CWWUC Presentation April 8, 2009

Step 4Fit Equation to Describe Interactions Between Stressors and Response

Use three-dimensional modeling program to identify specific non-linear relationship transformations

Page 33: CWWUC Presentation April 8, 2009

Fit Equation

Page 34: CWWUC Presentation April 8, 2009

Step 5Repeat Cycle if More Variables Are Needed

Enter the residuals calculated for the response variable into a new column in dataset.

The residuals are the remainder of the of the response variable after the variability caused by the 2 stressor variables is removed.

Repeat steps 2-4 to identify the next 2 important stressor variables.

Page 35: CWWUC Presentation April 8, 2009

Residuals From Equation Fitting

Page 36: CWWUC Presentation April 8, 2009

IIA Gives You . . .

An ordered list of stressors that are causing an impact on the response variables.

A model to help predict how the response variables will change based on a change in the stressor.

An understanding of whether habitat is playing a role in limiting the response variable.

A means to make sense of what the O/E and MMI metrics are showing and how that could relate to your discharge.

Page 37: CWWUC Presentation April 8, 2009

Questions