基于区间型贝叶斯模型的湟水干流水质评价

Water quality evaluation in Huangshui mainstream based on interval type Bayesian model

  • 摘要: 传统水质评价方法受主观因素影响较大,为进一步了解黄河上游重要支流湟水干流水质状况,根据2018年1—12月湟水干流12个断面的五日生化需氧量(BOD5)、化学需氧量(COD)、氨氮(NH3-N)、总磷(TP)、六价铬(Cr6+)等5项指标监测数据,采用区间型贝叶斯模型评价湟水干流水质状况。结果表明:区间型贝叶斯模型的排序结果能较为直观和准确地反映监测断面的水质变化情况,基本符合湟水从上游至下游呈“水质良好-水质恶化-水质好转”的水质变化趋势;湟水干流水质较差的断面基本位于人口集中、工业发达的城市集中河段,污染负荷大应是造成水质恶化的主要原因,未来应重点选择这些河段作为湟水水污染优先治理和水质监测的重点区域。

     

    Abstract: Traditional water quality evaluation methods are greatly affected by subjective factors. In order to further understand the water quality of the Huangshui mainstream in the upper reaches of the Yellow River, the interval type Bayesian model was used to evaluate water quality based on the monitoring data of BOD5, COD, NH3-N, TP and Cr6+ of 12 sections in the Huangshui mainstream from January to December 2018. The results show that the interval type Bayesian model can directly and accurately reflect the water quality change of monitoring sections, which basically accords with the trend in water quality of “good water quality-deteriorated water quality-improved water quality” from the upstream to the downstream of the Huangshui River. The sections with poor water quality are mainly located in the urban concentrated reaches with concentrated population and developed industries, and the excessive pollution should be the main reason for the deterioration of water quality. In the future, these reaches should be selected as the priority areas for water pollution control and water quality monitoring in the Huangshui River.

     

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