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引用本文:程月,李一平,施媛媛,唐春燕.大型浅水湖泊沉积成岩模型不确定性与敏感性分析——以氮为例.湖泊科学,2020,32(6):1646-1656. DOI:10.18307/2020.0607
CHENG Yue,LI Yiping,SHI Yuanyuan,TANG Chunyan.Uncertainty and sensitivity analysis of diagenesis model parameters in large shallow lakes—A case study on nitrogen. J. Lake Sci.2020,32(6):1646-1656. DOI:10.18307/2020.0607
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大型浅水湖泊沉积成岩模型不确定性与敏感性分析——以氮为例
程月1,2, 李一平1,2, 施媛媛1,2, 唐春燕1,2
1.河海大学环境学院, 南京 210098;2.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
摘要:
随着太湖流域控源截污和面源整治的推行,底泥释放成为太湖不可忽视的污染源.本文基于EFDC模型构建太湖沉积成岩模型以动态模拟底泥释放过程,以氨氮和硝态氮为水质目标,采用拉丁超立方抽样抽取沉积成岩模型的18个参数进行不确定性分析,采用标准秩逐步回归法进行敏感性分析.结果表明:对于大型浅水湖泊,沉积物-水界面的硝化作用、反硝化作用和扩散过程对底泥氮的释放影响很大,太湖氮浓度的不确定性有明显的时空差异,并且受藻类生长影响;随藻类生长生化反应参数的敏感性逐渐减弱,动力参数的敏感性逐渐增强,氨氮的主要敏感参数为孔隙水扩散系数和最优硝化反应速率,贡献率分别是41.68%和37.82%,硝态氮的主要敏感参数为孔隙水扩散系数和表层反硝化作用反应速率,贡献率分别是29.15%和42.34%,这些参数的取值需予以着重考虑.本研究识别出太湖底泥氮释放的关键物化过程,为模型调参提供优先级并给出优化区间,对减小模型的不确定性、提高模型精度有参考意义,为定性指导大型浅水湖泊底泥释放的室内实验模拟提供依据.
关键词:  太湖  浅水湖泊    底泥释放  不确定性  敏感性  沉积成岩
DOI:10.18307/2020.0607
分类号:
基金项目:国家重点研发计划项目(2017YFC0405203,2016YFC0401703)、国家水体污染控制与治理科技重大专项(2017ZX07204003)、国家自然科学基金项目(51579071,51779072,51809102)、创新研究群体科学基金项目(51421006)和中央高校基本科研业务费专项资金联合资助.
Uncertainty and sensitivity analysis of diagenesis model parameters in large shallow lakes—A case study on nitrogen
CHENG Yue1,2, LI Yiping1,2, SHI Yuanyuan1,2, TANG Chunyan1,2
1.College of Environment, Hohai University, Nanjing 210098, P. R. China;2.Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Ministry of Education, Hohai University, Nanjing 210098, P. R. China
Abstract:
With the implementation of source controlling and pollution intercepting in Taihu Basin, sediment has become a non-negligible pollution source in Lake Taihu. To simulate endogenous release dynamically, a diagenesis model based on EFDC model was established taking ammonia nitrogen and nitrate nitrogen as the water quality targets. The Latin hypercube sampling (LHS) was adopted to permute 200 combinations of 18 diagenesis model parameters, and the statistical method of probability distribution was applied to analyze uncertainty, similarly for standard rank stepwise regression method to identify sensitive parameters. The results showed that the nitrogen concentration was characterized by the spatial features that the uncertainty was greater in Meiliang Bay and the northwest lake area, and the temporal features that the uncertainty was largest in summer and then was in spring and winter. The uncertainty increased with the rise of the background concentration of water quality. The sensitive parameters for ammonia nitrogen were diffusion coefficient in porewater and reaction velocity for nitrification whose contribution rates to the uncertainty of ammonia nitrogen were 41.68% and 37.82% respectively. The sensitive parameters for nitrate nitrogen were diffusion coefficient in porewater and reaction velocity for denitrification in the aerobic layer, the contribution rates to the uncertainty of nitrate nitrogen were 29.15% and 42.34% respectively. The predominantly sensitive parameters were mainly related to nitrification, denitrification and diffusion process at sediment-water interface. With the growth of algae from dormancy to aggregation, the uncertainty of simulation results increased, and dominantly sensitive parameters turned from biochemical parameters to hydrodynamic parameters. The research discerned the key physicochemical processes and pivotal parameters in endogenous release in Lake Taihu, which can be references for further researches on the endogenous release of other nutrient such as carbon and silicon, and for the laboratory simulation qualitatively of endogenous release in large shallow lakes.
Key words:  Lake Taihu  shallow lake  nitrogen  endogenous release  uncertainty  sensitivity  diagenesis
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