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An ecological risk assessment paradigm using the Spatially
Integrated Model for Phosphorus Loading and Erosion (SIMPLE)
M.D. Matlock1,
D. E. Storm1, J. G. Sabbagh1,
C. T. Haan1, M. D. Smolen1
& S. L. Burks2
1Department of Biosystems
and Agricultural Engineering,
Oklahoma State University, Stillwater, OK 74078, USA
2Department of Zoology,
Oklahoma State University, Stillwater, OK 74078, USA
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Abstract
Ecological risk assessments provide a probabilitistic
approach to analyzing and predicting ecosystem responses to stress.
We are evaluating the relationship between nonpoint source (NPS)
phosphorus loading and the trophic status of the aquatic ecosystem.
We are using SIMPLE (the Spatially Integrated Model for Phosphorus
Loading and Erosion) to identify probable phosphorus sources in
a watershed, simulate the phosphorus loading to streams, and analyze
the relationships between input variables and their ecological impact.
The objective of this paper is to describe a risk-based paradigm
using SIMPLE to characterize the probability of exceeding a critical
phosphorus loading to a lotic ecosystem. We have characterized the
risk of exceeding a threshold loading of 0.5 kilogram total phosphorus
per hectare per year from a 2238 hectare watershed. Two-hundred-fifty
random SIMPLE simulations were performed to estimate annual total
phosphorus, dissolved phosphorus, and sediment-bound phosphorus
loading to a lotic ecosystem from the watershed. Simulation results
were analyzed statistically to determine the probabilities of exceeding
the critical loadings. Based on the current land use practices in
the Battle Creek watershed, the probability of exceeding the total
phosphorus critical loading rate of 0.5 kg/ha/yr was approximately
11 percent, or one year in nine the total annual loading will exceed
the critical loading rate. The 95 percent confidence intervals for
the total phosphorus loading occurring on average once in nine years
were relatively close (0.45 to 0.60 kg/ha/yr), assuming the only
variability from year to year was due to natural variability in
weather.
Keywords: ecological risk assessment, geographic information
systems
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