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An integrated model for simulating and diagnosing the water quality based on the system dynamics and Bayesian network

机译:基于系统动力学和贝叶斯网络的水质模拟与诊断集成模型

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摘要

An integrated model for simulating and diagnosing water quality based on the system dynamics and Bayesian network (BN) is presented in the paper. The research aims to connect water monitoring downstream with outlet management upstream in order to present an efficiency outlet management strategy. The integrated model was built from two components: the system dynamics were used to simulate the water quality and the BN was applied to diagnose the reason for water quality deterioration according to the water quality simulation. The integrated model was applied in a case study of the Songhua River from the Baiqi section to the Songlin section to prove its reasonability and accuracy. The results showed that the simulation fit to the variation trend of monitoring data, and the average relative error was less than 10%. The water quality deterioration in the Songlin section was mainly found to be caused by the water quality in the upper reach and Hadashan Reservoir drain by using the diagnosis function of the integrated model based on BN. The relevant result revealed that the integrated model could provide reasonable and quantitative support for the basin manager to make a reasonable outlet control strategy to avoid more serious water quality deterioration.
机译:提出了一种基于系统动力学和贝叶斯网络的水质模拟与诊断集成模型。该研究旨在将下游的水监控与上游的出水口管理联系起来,以提出一种高效的出水口管理策略。该集成模型由两部分组成:系统动力学用于模拟水质,BN用于根据水质模拟诊断水质恶化的原因。将该模型应用于百花至松林段的松花江流域,以证明其合理性和准确性。结果表明,仿真结果符合监测数据的变化趋势,平均相对误差小于10%。利用基于BN的综合模型的诊断功能,发现松林段水质恶化的主要原因是上游和哈达山水库排水的水质。相关结果表明,该综合模型可以为流域管理者制定合理的出水口控制策略提供合理和定量的支持,避免水质进一步恶化。

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