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Exploratory Data Analysis Techniques Applied to Hydrological Time Series. I: Self-Organizing Maps

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  21st Century Watershed Technology: Improving Water Quality and Environment Conference Proceedings, 29 March - 3 April 2008, Concepcion, Chile  701P0208cd.(doi:10.13031/2013.24291)
Authors:   Diego A Rivera, José L Arumí, Mario F Lillo
Keywords:   groundwater quality, data analysis, clustering, self-organizing maps, Piper Diagram

This paper adresses the application of self organizing maps for exploratory porpouses. Self- Organizing Maps allow to explore similarities in a data set collected at different location and/or moment. Two applications of Self- Organizing maps applied to groundwater quality data set are presented: Similary and discriminant capabilities for the identificaction of unknow samples, and the cooperative use with Piper Diagrams for cluster definition. These technique allows a process of exploratory data analysis, knowledge discovery and hypothesis construction rather han hypotesis testing. Also, further applications are discussed.

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