本研究的总体目标是评估比异味化合物更容易测量的水质参数是否可用于量化、表征和分析 管理味觉和气味（T&O）问题。实验方法和材料包括: 三种不同的原水（水质浓度的影响）； 1年以上的每周采样（季节性影响）；以及数据的统计处理。介绍了原水中某些水质参数的时间演变和平均浓度，以及使用水质参数在原水中建模geosmin和2-MIB，以及在原水中建模geosmin的人工神经网络。包括4个参考文献、图表。

The overall objective of this study was to evaluate whether water quality parameters, easier to measure than off-flavor compounds, can be used to quantify, characterize and manage taste and odor (T&O) problems. Experimental methods and materials included the following: three different raw waters (influence of water quality concentrations); weekly sampling over 1 year (seasonal effects); and, statistical treatment of data. Temporal evolution and mean concentration of some water quality parameters in raw waters is presented, along with modeling geosmin and 2-MIB in raw waters using water quality parameters, and artificial neural networks modeling of geosmin in raw waters. Includes 4 references, figures.