Neural Networks Predict Pesticide Leaching

by Steven K. Starrett, (A.M.ASCE),
Shelli K. Starrett,
Yacoub M. Najjar, (A.M.ASCE),
Judy C. Hill, (S.M.ASCE),



Document Type: Proceeding Paper

Part of: North American Water and Environment Congress & Destructive Water

Abstract:

The goal of this work was to determine whether artificial neural networks (ANN) can be used to predict the percentage of applied pesticide that leaches through 50 cm of turfgrass covered soil. One-hundred seventy-five sets of data were used to train the ANN. After training, a simulation of 25 test cases were run. We were pleased with the ANN predictions for this initial study. The ANN appears to be reasonably able to predict the percentage of pesticide that leached through 50 cm of turigrass covered soil. Future work consists of incorporating additional data sets into the training and testing process of this ANN.

Subject Headings: Neural networks | Pesticides | Soil pollution | Leaching | Vegetation | Training | Information management

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