An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment
An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment
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DOI：
10.1016/j.jcp.2014.11.035
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发表时间：
2015-02
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影响因子：
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通讯作者：
G. Manoli;M. Rossi;D. Pasetto;R. Deiana;S. Ferraris;G. Cassiani;M. Putti
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文献类型：
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作者：
G. Manoli;M. Rossi;D. Pasetto;R. Deiana;S. Ferraris;G. Cassiani;M. Putti
非饱和地下水流的建模受到与测量和模型误差相关的高度不确定性的影响。电阻率层析成像（ERT）等地球物理方法可以提供有关包气带中发生的水文过程的有用间接信息。本文提出并验证了一种迭代粒子滤波方法来求解耦合水文地球物理反问题。我们专注于一个渗透试验监测的时间推移ERT和建模使用理查兹方程。目的是从ERT电位测量值中识别水文模型参数。传统的非耦合反演需要求解两个连续的反问题，第一个反问题应用于ERT测量，第二个反问题应用于理查兹方程。这种方法不能确保物理状态的准确定量描述，通常违反质量平衡。为了避免这两个反演之一，并在此过程中纳入更多的物理模拟约束，我们投的SIR（顺序重要性恢复）的数据同化方法，使用理查兹方程求解器模型的水文动力学和前向ERT模拟器结合阿尔奇定律作为测量模型的框架内的问题。ERT观察，然后用于更新系统的状态，以及估计模型参数和它们的后验分布。针对传统序贯贝叶斯方法的局限性，提出了一种新的迭代方法来高精度地估计模型参数。所开发的算法的数值特性进行了验证，均质和非均质的合成测试用例的基础上，在现实世界的现场实验。
The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archie's law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.