自相似枝状河网污染物输移掺混机理及多源反演识别研究

项目名称： 自相似枝状河网污染物输移掺混机理及多源反演识别研究

项目编号： No.51479064

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 其他

项目作者： 刘晓东

作者单位： 河海大学

项目金额： 78万元

中文摘要： 掌握污染物在天然河网中的输移掺混特性、准确获取污染源信息对河网地区水污染控制至关重要。本项目基于分形理论和Horton定律分析河网自相似形态特征，在此基础上遴选典型枝状河网试验小区，利用野外示踪试验揭示不同污染源排放方式下典型天然枝状河网污染物输移规律；结合自相似二级枝状河网物理模型试验，剖析河网多级交汇水动力特性对污染物输运扩散的驱动机理，阐释不同入汇角、入流比和长度比等形态特征因子对污染物输移的影响机制；从反问题角度，针对河网水环境系统的不确定性，将广义贝叶斯估计方法、数据驱动模型与河网水质模型相耦合，提出基于广义贝叶斯估计的河网污染源与参数同步反演识别方法；针对监测数据不确定所导致的反问题不适定性,建立一定资源总量约束下监测资源分配优化模型,探讨多源耦合作用下河网污染源反问题的适定性条件。研究成果为河网水环境模拟提供理论基础，同时为河网污染源信息获得提供新的手段。

中文关键词： 自相似；反问题；污染物输移；源识别；枝状河网

英文摘要： It is very necessary for the control of water pollution to master the transport and mixing properties and obtain pollution sources information accurately in river network area. Based on fractal theory and Horton law, the self similar morphological features of natural river network will be analyzed and then typical dendritic network area will be selected to study. Pollutant transport mechanism in elected natural river network area will be discussed by using the field test. A self similar two-branched River physical model will be constructed to analyze driving mechanism between hydrodynamic characteristics and pollutant transportation. The effect of diversion angle, branching ratio, flow ratio and length ratio on the pollutant transport characteristics will be revealed. An inversion method on identification of pollution source and parameters will be proposed by river water quality model coupled with generalized Bayesian estimation method and data driven model for water environmental system uncertainties. A optimization model of monitoring resource allocation will also be established, and the well-posedness of the inverse problem of river pollution source under the condition of multiple sources will be discussed to solve ill posed problem caused by the uncertainty of observed dada. The research results will provide theoretical basis for water environmental simulation, at the same time provide a new mean to obtain river pollution source information.

英文关键词： Self Similarity;Inverse Problem;Pollutant Transport;Source Identification;Dendritic River Networks