A System Dynamic Model and Sensitivity Analysis for Simulating Domestic Pollution Removal in a Free-Water Surface Constructed Wetland
A System Dynamic Model and Sensitivity Analysis for Simulating Domestic Pollution Removal in a Free-Water Surface Constructed Wetland
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模拟自由水面人工湿地生活污染去除的系统动态模型及敏感性分析
DOI：
10.1007/s11270-011-1062-8
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
W. Ou
中科院分区：
文献类型：
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作者：
Yung;Yu;Chun;L. Chiang;Hone‐Jay Chu;W. Ou
建立了自由水面人工湿地系统动力学模拟模型，并为人工湿地的管理参数提供了合理的取值。系统动力学模型的校准和验证，使用的数据从一个人工湿地在台湾南部的台南市为期1年的研究。此外，通过广义似然不确定性估计（GLUE）的敏感性分析，获得影响仿真输出的主要参数。模型模拟出的出水量与实测出水量之间具有较高的R2和Nash-Sutcliffe效率系数，表明该模型除了能再现溶解氧（DO）、5 d生物需氧量（BOD5）、总氮（TN）、总悬浮泥沙（TSS）和总磷（TP）浓度的变化趋势外，还能模拟DO、BOD5和TSS的变化。考虑到参数间的相互作用，GLUE方法成功地从Monte Carlo参数集中获得了模型敏感参数。敏感性分析结果表明，微生物参数是影响DO、BOD5和TN的敏感因子，而底泥粒径对TP和TSS影响较大。对环境微生物的进一步研究将提高模型的准确性，为人工湿地的管理和设计提供有价值的参考。
This work develops a system dynamic simulation model for free-water surface constructed wetlands, as well as provides appropriate values for the parameters of constructed wetland management. The system dynamic model is calibrated and validated by using data from a 1-year study of a constructed wetland in Tainan of southern Taiwan. Additionally, the major parameters that affect the simulation output are obtained via sensitivity analysis by using generalized likelihood uncertainty estimation (GLUE). A highR2and Nash–Sutcliffe coefficient of efficiency between the simulated and measured outflow values indicate that in addition to reproducing the changing trends of dissolved oxygen (DO), 5-day biological oxygen demand (BOD5), total nitrogen (TN), total suspended sediment (TSS), and total phosphorous (TP) concentrations, the model can simulate the variations of DO, BOD5, and TSS. Taken into account the interactions among parameters, the GLUE method successfully obtained the model sensitive parameters from the Monte Carlo parameter sets. Sensitivity analysis results indicate that the parameters of microorganisms are sensitive factors that affect DO, BOD5, and TN, while sediment diameter largely influences TP and TSS. Further elucidating environmental microorganisms would increase the model accuracy and provide a valuable reference for constructed wetland management and design.