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Determining the decision-making risk from AGNPS simulations

Parson, S.C. / Hamlett, J.M. / Robillard, P.D. / Foster, M.A.

The probabilistic Agricultural Nonpoint Source Pollution Model (AGNPS) was applied to the Hazelton drain subwatershed of the Sycamore Creek watershed in southcentral Michigan. Eight AGNPS input file scenarios were created with the hydrologic unit/water quality tool. For each AGNPS scenario, the Monte Carlo method produced 1000 AGNPS simulations for each input variation level. This created 1000 AGNPS output files, from which were extracted the values for sediment yield, sediment nitrogen, sediment phosphorus, soluble nitrogen, soluble phosphorus, soluble chemical oxygen demand, and runoff volume at the subwatershed outlet. Decisions made using water-based outputs evidence much less risk than those decisions based on sediment-based outputs.

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Determining the decision-making risk from AGNPS simulations

Parson, S.C. / Hamlett, J.M. / Robillard, P.D. / Foster, M.A.

The probabilistic Agricultural Nonpoint Source Pollution Model (AGNPS) was applied to the Hazelton drain subwatershed of the Sycamore Creek watershed in southcentral Michigan. Eight AGNPS input file scenarios were created with the hydrologic unit/water quality tool. For each AGNPS scenario, the Monte Carlo method produced 1000 AGNPS simulations for each input variation level. This created 1000 AGNPS output files, from which were extracted the values for sediment yield, sediment nitrogen, sediment phosphorus, soluble nitrogen, soluble phosphorus, soluble chemical oxygen demand, and runoff volume at the subwatershed outlet. Decisions made using water-based outputs evidence much less risk than those decisions based on sediment-based outputs.

Determining the decision-making risk from AGNPS simulations

Parson, S.C. / Hamlett, J.M. / Robillard, P.D. / Foster, M.A.

The probabilistic Agricultural Nonpoint Source Pollution Model (AGNPS) was applied to the Hazelton drain subwatershed of the Sycamore Creek watershed in southcentral Michigan. Eight AGNPS input file scenarios were created with the hydrologic unit/water quality tool. For each AGNPS scenario, the Monte Carlo method produced 1000 AGNPS simulations for each input variation level. This created 1000 AGNPS output files, from which were extracted the values for sediment yield, sediment nitrogen, sediment phosphorus, soluble nitrogen, soluble phosphorus, soluble chemical oxygen demand, and runoff volume at the subwatershed outlet. Decisions made using water-based outputs evidence much less risk than those decisions based on sediment-based outputs.

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Title:

Determining the decision-making risk from AGNPS simulations

Contributors:

Parson, S.C. (author) / Hamlett, J.M. (author) / Robillard, P.D. (author) / Foster, M.A. (author)

Published in:

Transactions of the ASAE ; 41 ; 1679-1688

Publication date:

1998

Size:

10 Seiten, 43 Quellen

ISSN:

Type of media:

Article (Journal)

Type of material:

Print

Language:

English

Keywords:

Monte-Carlo-Methode , Rechnersimulation , mathematisches Modell , Risikoanalyse , statistische Verteilung , Sediment , Stickstoff , Phosphor , chemischer Sauerstoffbedarf , Wasserqualität

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