Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells
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Abstract
A neural network analysis of agrichemical occurrence in groundwater was conducted using data from a pilot study of 192 small-diameter drilled and driven wells and 115 dug and bored wells in Illinois, a regional reconnaissance network of 303 wells across 12 Midwestern states, and a study of 687 domestic wells across Iowa. Potential factors contributing to well contamination (e.g., depth to aquifer material, well depth, and distance to cropland) were investigated. These contributing factors were available in either numeric (actual or categorical) or descriptive (yes or no) format. A method was devised to use the numeric and descriptive values simultaneously. Training of the network was conducted using a standard backpropagation algorithm. Approximately 15% of the data was used for testing. Analysis indicated that training error was quite low for most data. Testing results indicated that it was possible to predict the contamination potential of a well with pesticides. However, predicting the actual level of contamination was more difficult. For pesticide occurrence in drilled and driven wells, the network predictions were good. The performance of the network was poorer for predicting nitrate occurrence in dug and bored wells. Although the data set for Iowa was large, the prediction ability of the trained network was poor, due to descriptive or categorical input parameters, compared with smaller data sets such as that for Illinois, which contained more numeric information.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells |
Series title | Journal of Hydrologic Engineering |
DOI | 10.1061/(ASCE)1084-0699(2004)9:6(502) |
Volume | 9 |
Issue | 6 |
Year Published | 2004 |
Language | English |
Publisher | American Society of Civil Engineers |
Contributing office(s) | Iowa Water Science Center, Toxic Substances Hydrology Program |
Description | 10 p. |
First page | 502 |
Last page | 511 |
Country | United States |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |