predicting acid neutralizing capacity for the mid-atlantic highlands region
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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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N = 238
Distribution of ANC by Geologic Class
Argillace Carbonate Felsic Mafic Siliceous
class
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AN
C
NAArgillaceCarbonateFelsicMaficSiliceousUnclassif
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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Cor
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Omnidirectional Correlgram of residuals
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Euclidean distance between points
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Cor
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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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Plot of Resids vs. log(Pasture)
log(Urb.hi)
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Plot of Resids vs. log(Urb.hi)
Elevation
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Plot of Resids vs. Elevation
Tue Sep 17 12:26:51 2002
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
Tue Sep 17 12:26:51 2002
Fitted values
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Plot of Resids vs. Fitted Values
Quantiles of Standard Normal
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QQ plot of Residuals
Tue Sep 17 12:26:51 2002
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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
xp
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Directional Correlogram of residuals w/ X and Y50 degree angle, 10 degrees span
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