【摘要】 现有年度水质评价采用的是各指标浓度的年均值,当水体出现短时高质量污染时,不能准确反映全年整体水质状况,且当各年度水质等级相同时,不易进行年际变化分析。针对以上问题,研究提出了基于区间型贝叶斯的年度水质评价方法。将每个水质指标全年实际监测浓度以区间数的形式表示,用贝叶斯公式计算出多个后验概率区间值,根据可能度排序方法对多个区间值进行比较,以最大后验概率区间值确定水质类别。在此基础上,对具有相同等级的水质则按照其综合属性区间值进行排序,确定其年际变化状况。将该方法运用于青衣江洪雅段龟都府断面年度水质评价中,得到该断面2011～2016年水质状况较好,均达到I类水质标准;2012年水质较2011年有所改善,并优于其他年份,但此后2013～2016年水质逐年变差,总体水质有恶化的趋势。更多还原

【Abstract】 The traditional water quality assessment methods use annual average concentration of various pollution indicator, which is difficult to accurately reflect the general water quality status when short-term high pollution emerges and is also hard to carry out inter-annual analysis when the water quality in different years are in a same pollution level. In the light of the above problems, in this study, an Interval-Bayesian Water Quality Evaluation Method is developed by introducing the interval number theory into traditional Bayesian method. The annual monitoring concentration of each water quality indicator is expressed in the form of interval number and the posterior probability interval values are calculated by Bayesian formula. The water quality grade is determined based on maximum interval values and the water quality interannual variability is analyzed according to ranking-method of interval number. The new method is applied to analyze the interannual water quality trend of Guidufu cross-section in Hongya reach of the Qingyi River. The result show that the water quality of the cross-section from year 2011 to 2016 was good and all met the Class I grade; the water quality in 2012 was better than that in 2011 and other years. However, the water quality from year 2013 to 2016 deteriorated year by year. The overall water quality showed a trend of deterioration.更多还原