Predicting Acid Neutralizing Predicting Acid Neutralizing Capacity for the Mid-Atlantic Capacity for the Mid-Atlantic

Highlands RegionHighlands RegionBrett Kellum

Jennifer Hoeting

N. Scott Urquhart

Colorado State University

September 21, 2002

FUNDING SOURCE

• This presentation was developed under the STAR Research Assistance Agreement CR-829095 awarded by the U.S. Environmental Protection Agency (EPA) to Colorado State University.  This presentation has not been formally reviewed by EPA.  The views expressed here are solely those of its authors and the STARMAP Program. EPA does not endorse any products or commercial services mentioned in this presentation.

IntroductionIntroduction

A. What is Acid Neutralizing Capacity (ANC)?

B. Remotely sensed model predictors

C. Data source: EMAP - Mid-Appalachian Highlands Region Assessment

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ANC

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Distribution of ANC by Geologic Class

Argillace Carbonate Felsic Mafic Siliceous

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ANC Sites by Available GeologyANC Sites by Available Geology

Location and Magnitude of ANC in MAHA region

Predictors Considered for ModelPredictors Considered for Model

• Elevation

• Bedrock Geology (with 5 classes)

• 13 Thematic Mapper Imagery Classifications

• Alber’s Projection Coordinates

• Strahler Order

Final data set contains 238 sites

Response:

Acid Neutralizing Capacity (log)

Final Predictors in current “best” Regression Model Final Predictors in current “best” Regression Model

(Transformations)(Transformations)

Predictors:% Probable Row Crops% Pasture (log)% Urban – High Density (log)% Emergent Wetlands (log)% Woody Wetlands (log)% QuarryElevationCarbonate BedrockFelsic Bedrock

Model Summary

R2 = 0.58

Overall p-value <.0001

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Euclidean distance between points

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Omnidirectional Correlgram of residuals

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Euclidean distance between points

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Directional Correlogram of residuals50 degree angle, 10 degrees span

V. Areas of Further ResearchV. Areas of Further Research

A. More work in the area of anisotropic spatial models

B. Including interaction terms in the model

C. Weighted Least Squares

D. Predictive ability of models in other areas of MAHA

Probable

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Plot of Resids vs. Probable

log(Pasture)

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log(Urb.hi)

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Plot of Resids vs. log(Urb.hi)

Elevation

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Quarry

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Plot of Resids vs. Quarry

log(Emergent)

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Plot of Resids vs. log(Emergent)

log(Woody)

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Plot of Resids vs. log(Woody)

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Plot of Resids by carbon and felsic geology

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Fitted values

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Quantiles of Standard Normal

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Acid Neutralizing Capacity

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Histogram of Acid Neutralizing Capacity From Full MAHA Data

Coefficients: Value Pr(>|t|) (Intercept) 7.8 <.0001pasture 0.0361 0.0169probable 0.0133 0.0184row.crops 0.0102 0.5017decid -0.0025 0.3589mixed 0.0554 0.1624evergreen -0.0210 0.1991urb.hi 0.0437 0.0713urb.low 0.0247 0.1898emergent 0.0559 0.0160woody -0.0468 0.0203transition -0.0030 0.8109quarry 0.0113 0.4649water -0.0110 0.5110elev -0.0007 0.0006carbon 0.4408 0.0302felsic -0.2392 0.2233arg 0.0356 0.8480silic -0.0211 0.9144ord2 -0.1206 0.1630ord3 -0.1471 0.1355X -0.0841 0.1223Y -0.0846 0.0649X^2 0.0058 0.8951Y^2 -0.1141 0.0155X*Y 0.1067 0.0748

Multiple R-Squared: 0.6394 Overall p-value is <.0001

Coefficients:

Value Pr(>|t|)

(Intercept) 7.4355 <.0001

probable 0.0119 0.0008

pasture 0.0529 <.0001

urb.hi 0.0686 0.0002

emergent 0.0446 0.0369

woody -0.0694 0.0003

quarry 0.0260 0.0750

elev -0.0005 0.0007

carbon 0.5215 <.0001

felsic -0.2935 0.0040

Multiple R-Squared: 0.5784

Overall p-value is <.0001

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Directional Correlogram of residuals w/ X and Y50 degree angle, 10 degrees span