4? EPA Science Forum

Multiple Scale Nitrogen Loading Risks TI_ *?fr of wfier:

- '	.	- u	, _r -	Thirty Years of Progress

Across a Large Geographic Region Through Partnering

Anne C. Neale1, K. Bruce Jones1, Timothy G. Wade2, James D. Wickham2, Maliha S. Nash1, Curtis M. Edmonds1, & Rick D. Van Remortei3

'U.S. Environmental Protection Agency, Las Vegas, Nevada; 2U.S. Environmental Protection Agency, Research Triangle Park, North Carolina; 3l.ockheed-Martin, Las Vegas, Nevada

Landscape Metrics Evaluated in the
Statistical Analysis

Mean Riparian agriculture

Riparian forest

Forest fragmentation

Road density

Forest land cover

Agricultural land cover

Agricultural land cover on steep slopes

Nitrate deposition

Potential soil loss

Roads near streams

Slope gradient

Slope gradient range

Slope gradient variance

Urban land cover

Wetland land cover

Barren land cover

Example Watershed

Landscape m? tries calculated on each watershed

PROBLEM STATEMENT

APPROACH

•	Develop models that use satellite imagery and other spatial data to predict potential TMDL exceedance

•	Conduct analysis and develop the model in the "data rich" Mid-Atlantic Region (477 watersheds)

•	Use existing data on nitrogen concentrations in streams from the Environmental Monitoring and
Assessment Program (EMAP) and STORET, atmospheric nitrate deposition from the EPA, and spatial data
on land cover (National Land Cover Database or NLCD), soils (USDA STATSGO), and topography (Digital
Elevation Models) to develop the model

•	Use Regression Tree Analysis to establish quantitative relationships between land surface conditions,
atmospheric nitrate deposition, and total nitrogen concentrations in streams

Partnering to Protect Human

• Current approaches to list streams and water bodies as
impaired under Section 303(d) of the Clean Water Act are
highly fragmented and inconsistent, making Total
Maximum Daily Load (TMDL) listings scientifically indefen-
sible

• Method needs to
identify likely caus-
es of impairment
and how the caus-
es vary in their
importance in dif-
ferent biophysical
settings. This is
important in identi-
fying management
options needed to
improve conditions

FINDINGS

• Landscape metrics did a good job
of predicting the relative levels of
total nitrogen concentrations in
streams (60% of variance
explained) using regression tree
analysis

Li _!~ si =g

Riparian forest improves water
r wrr|Yrj quality in an urban setting

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• Information and the statistical modeling approach provided in
this study can be used by environmental managers to evalu-
ate and revise TMDL lists of water bodies relative to nitrogen
concentration across the Mid-Atlantic Region and to propose
potential ways to reduce risks

• There were differences in the
importance of landscape conditions
in different parts of the Region

-	Streams with the greatest concen-
tration of nitrogen were generally
in the northern part of the Region
and in areas with high amounts of
agricultural lands

-	In northern parts of the Region it
took higher amounts of forest to
mitigate impacts of high amounts
of atmospheric nitrate deposition

-	Forested riparian areas were
effective in reducing stream nitro-
gen concentration but generally in
areas with lower atmospheric
nitrate deposition

Regression tree analysis results

Sampling locations, color indicates
terminal node designation from
regression tree analysis

Lack of scientific rigor and objectivity has led to several
pending court cases

Need for comprehensive and objective method to identify
streams and other water bodies that have a high potential
of exceeding Total Maximum Daily Load (TMDL) thresh-
olds at regional
scale

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