Type curve matching method is a graphical procedure for evaluating aquifer parameters form pumping test data. This method involves matching field data with a “type curve” calculated from the analytical equation of the selected pumping test conditions. However, it is time consuming of plotting data and an individual error is likely to occur in the fitting the type curve and identifying a match point. A new approach to pumping test analysis procedure is presented which evaluates the drawdown data curves with the aid of type curve matching technique using artificial neural networks (ANN). In our proposed method the pattern-matching capability of ANN is used. The ANN is trained to recognize several type curves presented for pumping test conditions in a leaky confined aquifer. This ANN system can classify measured time-drawdown curves into the typical patterns and estimate adequate hydraulic properties. The hypothetical and actual time-drawdown data sets from pumping tests for a leaky aquifer are used to evaluate availability of our proposed method.

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To investigate the adsorbability of organic contaminants on original Aso volcanic ash soil, the removal volatile organic compounds (VOC), pesticides components in the monitoring items and the environmental quality standard items in the Kankyou-kihon-hou adsorbed on the soil packed in a large column were examined in this paper. The results showed that their adsorbability was influenced by water solubility of organic contaminants and the number and kinds of hydrophilic functional groups in the compounds.

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