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引用本文:姜龙,李一平,章双双,王文才,翁晟琳,杜薇,王建威.大型浅水湖泊藻类模型参数敏感性分析.湖泊科学,2018,30(3):693-700. DOI:10.18307/2018.0311
JIANG Long,LI Yiping,ZHANG Shuangshuang,WANG Wencai,WENG Shenglin,DU Wei,WANG Jianwei.Parameter sensitivity analysis of algal model in large shallow lakes. J. Lake Sci.2018,30(3):693-700. DOI:10.18307/2018.0311
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大型浅水湖泊藻类模型参数敏感性分析
姜龙1,2, 李一平1,2, 章双双3, 王文才4, 翁晟琳1,2, 杜薇5, 王建威6
1.河海大学浅水湖泊综合治理与资源开发教育部重点实验室, 南京 210098;2.河海大学环境学院, 南京 210098;3.苏州科技大学, 苏州 215009;4.环境保护部华南环境科学研究所, 广州 510655;5.环境保护部南京环境科学研究所, 南京 210042;6.中国电建集团华东勘测设计研究院有限公司, 杭州 310014
摘要:
选取太湖作为典型湖泊在之前研究基础上建立藻类模型,对模型中与藻类有关的40个参数进行拉丁超立方抽样,并使用区域敏感性分析方法和普适似然不确定性分析方法进行敏感性分析.结果表明:在所选的40个参数中,有7个参数是敏感的参数,对模拟的结果影响较大.在藻类生长、基础代谢、牧食和沉降4个藻类变化过程中藻类生长的敏感参数最多,影响最大;在藻类生长项中,叶绿素的消光系数是藻类生长光照限制中的最敏感参数,而最低适宜生长温度及其对藻类生长的影响系数则是温度限制中的敏感参数;并且不同湖区的不确定性在不同时间差异明显,对于藻类低浓度湖区和藻类暴发期的模拟需要加以关注.
关键词:  太湖  区域敏感性分析方法(RSA)  普适似然不确定性分析方法(GLUE)  参数敏感性  藻类模型
DOI:10.18307/2018.0311
分类号:
基金项目:国家自然科学基金项目(5177090079,51579071,51539003)、国家重点研发计划项目(2016YFC0401703)和创新研究群体科学基金项目(51421006)联合资助.
Parameter sensitivity analysis of algal model in large shallow lakes
JIANG Long1,2, LI Yiping1,2, ZHANG Shuangshuang3, WANG Wencai4, WENG Shenglin1,2, DU Wei5, WANG Jianwei6
1.Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing 210098, P. R. China;2.College of Environment, Hohai University, Nanjing 210098, P. R. China;3.Suzhou University of Science and Technology, Suzhou 215009, P. R. China;4.South China Institute of Environmental Science, Guangzhou 510655, P. R. China;5.Nanjing Institute of Environmental Science, Ministry of Environmental Protection, Nanjing 210042, P. R. China;6.HydroChina Huadong Engineering Corporation, Hangzhou 310014, P. R. China
Abstract:
Lake Taihu was chosen as it is a typical large shallow lake, and algal model was established. 40 parameters in water quality model of the lake were filtered by previous research and sampled with Latin hypercube sampling method, and regionalized sensitivity analysis method and generalized likelihood uncertainty estimation method applied for uncertainty and sensitivity analysis, respectively. The results show that only 7 parameters selected were sensitive, and algal growth was the most important factor between the growth, basic metabolism, predation and settlement of algae. The extinction coefficient of chlorophyll was the most sensitive parameters in the light limitation of algae growth, and suboptimal temperature effect coefficient for growth also turned to be sensitive in the temperature limitation. In addition, uncertainty distinguished in different areas and period, more attention should be paid on low concentration areas and periods of algal blooms.
Key words:  Lake Taihu  regionalized sensitivity analysis  generalized likelihood uncertainty estimation  parameter sensitivity  algal model
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