A new inverse method for contaminant source identification under unknown solute transport boundary conditions
A new inverse method for contaminant source identification under unknown solute transport boundary conditions
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未知溶质运移边界条件下污染源识别的新逆方法
DOI：
10.1016/j.jhydrol.2019.123911
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发表时间：
2019
影响因子：
6.4
通讯作者：
Wang, Liqiang
中科院分区：
文献类型：
--
作者：
Jiao, Jianying;Zhang, Ye;Wang, Liqiang
提出了一种新的溶质运移反演方法，用于在稳态、非均匀地下水流场中未知溶质运移边界条件下估算羽流轨迹和源释放位置。溶质浓度的建模提出了一组局部近似解（LAS）的运输离散化的问题域。在一个给定的时间步长，逆方法施加连续的浓度和总溶质质量通量在反演网格中的一组配置点，而LAS的条件下测得的突破浓度。通过在空间和时间中的选定点处实施传输物理，逆问题变得适定，并且逆方程的单个系统被组装并用并行迭代求解器求解。与最小化模型-数据失配目标函数的大多数反演技术不同，反演方法不需要模拟用于优化的正向输运模型，因此可以恢复溶质初始和边界条件。假设分散性估计是可用的，该方法使用来自各种采样密度和设计的合成突破数据进行了演示，即，不规则井网与均匀井网。不同的测量误差和源释放历史（例如，时间上均匀的、单个和多个脉冲）。结果表明，对于所测试的源释放历史，1）在最大观测浓度的5%的测量误差下，反演是稳定的; 2）通过溶质穿透浓度可以精确估计烟羽轨迹和源释放位置; 3）反演精度对采样井密度及其信息含量最为敏感。
A new solute transport inverse method is proposed for estimating plume trajectory and source release location under unknown solute transport boundary conditions in a steady-state, non-uniform groundwater flow field. Solute concentration is modeled by proposing a set of local approximation solutions (LAS) of transport that are discretized over the problem domain. At a given time step, the inverse method imposes continuities of concentration and total solute mass flux at a set of collocation points in the inversion grid, whereas the LAS are conditioned to measured breakthrough concentrations. By enforcing transport physics at selected points in space and time, the inverse problem becomes well-posed and a single system of inversion equations is assembled and solved with a parallel iterative solver. Unlike most of the inversion techniques that minimize a model-data mismatch objective function, the inverse method does not require the simulation of a forward transport model for optimization, thus both solute initial and boundary conditions can be recovered. Assuming dispersivity estimates are available, the method was demonstrated using synthetic breakthrough data from various sampling densities and designs, i.e., irregular versus uniformly spaced well networks. Different measurement errors and source release histories (e.g., uniform-in-time, single, and multiple pulses) were also investigated. Results suggest that for the source release histories tested, 1) inversion is stable under increasing measurement errors up to 5% of the maximum observed concentration; 2) accurate plume trajectory and source release location can be estimated from solute breakthrough concentrations; 3) inversion accuracy appears the most sensitive to sampling well density and its information content.
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影响因子：
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影响因子：
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