Graduate School of Engineering, Hokkaido University, N13W8, Sapporo 060-8628, Japan.
Water Res. 2012 Mar 1;46(3):741-9. doi: 10.1016/j.watres.2011.11.036. Epub 2011 Nov 25.
Measuring river water concentrations of all pesticides applied in a catchment area is a daunting task. This study aims to develop new score tables for selecting analytical target pesticides. Sensitivity analyses were conducted using a diffuse pollution hydrologic model to quantitatively evaluate the influence of pesticide properties (e.g., log K(OC), degradability [half-life]) on concentrations of rice-farming pesticides in river water. Using the results of the analyses, score tables were systematically designed for the pesticide properties such that the sum of the scores for a particular pesticide, designated as the contamination index, was proportional to the expected/predicted concentration of that pesticide in river water. The contamination indexes for pesticides applied in three river basins were calculated and compared with the corresponding observed pesticide concentrations. Correlations between contamination indexes and observed concentrations were fairly good. Pesticides were ranked according to the quotients obtained by dividing the pesticide concentrations predicted from the contamination indexes by the corresponding drinking-water quality guideline values, and pesticide candidates to be monitored were successfully selected on the basis of a threshold quotient.
测定集水区内所有施用农药的河流水浓度是一项艰巨的任务。本研究旨在开发新的评分表，以选择分析目标农药。使用漫射污染水文学模型进行了敏感性分析，以定量评估农药性质（如 log K(OC)、降解性[半衰期]）对稻田农药在河水中浓度的影响。利用分析结果，系统地为农药性质设计了评分表，使得特定农药的评分总和（指定为污染指数）与该农药在河水中的预期/预测浓度成正比。计算了在三个流域施用的农药的污染指数，并将其与相应的观测农药浓度进行了比较。污染指数与观测浓度之间的相关性相当好。根据从污染指数预测的农药浓度与相应饮用水质量指导值的商数对农药进行了排序，并根据阈值商数成功地选择了要监测的农药候选物。
