| 引用本文: | 赵英,郭亮.贝叶斯方法的污染源季节性排放量控制和管理[J].哈尔滨工业大学学报,2014,46(12):26.DOI:10.11918/j.issn.0367-6234.2014.12.005 |
| ZHAO Ying,GUO Liang.A seasonal management method for controlling pollution sources discharge based on Bayesian method[J].Journal of Harbin Institute of Technology,2014,46(12):26.DOI:10.11918/j.issn.0367-6234.2014.12.005 |
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| 摘要: |
| 为保证水质功能区内水质达标,必须对区域内污染源排放量进行控制和管理. 选取松花江哈尔滨段主要污染指标COD和氨氮为研究对象,利用一维水质模型构建各污染源排放量与河流水质之间的关系. 用贝叶斯方法估计水质模型中的重要参数综合降解系数（k）,根据估计时期的不同,分别建立季节模型和年度模型,用以控制既定水质目标下各污染源排放量. 结果表明,季节模型的预测效果较好,能更好地表达水中污染物的综合降解浓度. 应用季节模型和贝叶斯方法开展季节性水质管理工作,可以提供给决策者更多的信息,有助于对污染源排放量的不确定性进行量化和评估. 此外,通过对比各污染源的削减水平,可得各污染源在不同时期的控制权重,从而使管理者在不同时期有针对性地对污染源排放量进行控制. 贝叶斯方法在污染源排放量控制中的应用可以增强水质模型的预测能力,有效提高水质管理的水平. |
| 关键词: 贝叶斯方法 不确定性 污染源管理 季节模型 水质管理 |
| DOI：10.11918/j.issn.0367-6234.2014.12.005 |
| 分类号:X703.5 |
| 基金项目:国家自然科学基金青年基金(71203041);中国博士后科学基金(20110491056);黑龙江省博士后基金(LBH-Z10172);哈尔滨工业大学创新基金(2011年)． |
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| A seasonal management method for controlling pollution sources discharge based on Bayesian method |
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ZHAO Ying1,2, GUO Liang1,2
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(1. School of Municipal and Environmental Engineering, Harbin Institute of Technology, 150090 Harbin, China; 2. State Key Laboratory of Urban Water Resource and Environment(Harbin Institute of Technology), 150090 Harbin, China)
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| Abstract: |
| Ammonia and COD are selected as study variables for they are the main water quality parameters and can represent water environment quality of the Harbin City Reach of the Songhua River. One-dimensional water quality model is used to set up the relationship of pollutant loadings and water quality. The comprehensive decay rate (k), a key parameter of water quality model, is estimated by Bayesian method. The seasonal model and annual model are respectively set up according to different k estimated in different period. The pollutant loadings are controlled by the models for downriver water quality can meet targeted goals. From contrasting the two models, it indicates that predicting precision of seasonal model is high than annual model for seasonal model can better express comprehensive degradation concentration of ammonia in water. Contrasting with other methods, water quality management with seasonal model can offer decision makers more useful information, and help them address uncertainties. In addition, influencing weights of the three pollution sources can be obtained by contrasting load reduced ratios. The information could inform decision makers of the required load reductions for the three time periods. |
| Key words: Bayesian uncertainty pollution sources controlling seasonal model water quality management |
