[1] Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. However, their usefulness is largely limited by the inherent assumption of Gaussian error statistics. Hydraulic conductivity distributions in alluvial aquifers, for example, are usually non-Gaussian as a result of complex depositional and diagenetic processes. In this study, we combine an ensemble Kalman filter with grid-based localization and a Gaussian mixture model (GMM) clustering techniques for updating high-dimensional, multimodal parameter distributions via dynamic data assimilation. We introduce innovative strategies (e.g., block updating and dimension reduction) to effectively reduce the computational costs associated with these modified ensemble Kalman filter schemes. The developed data assimilation schemes are demonstrated numerically for identifying the multimodal heterogeneous hydraulic conductivity distributions in a binary facies alluvial aquifer. Our results show that localization and GMM clustering are very promising techniques for assimilating high-dimensional, multimodal parameter distributions, and they outperform the corresponding global ensemble Kalman filter analysis scheme in all scenarios considered.

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This paper presents a method for calculating the effective stagnant thermal conductivity of consolidated porous media with multiphase fluid saturation. The method takes into account the pore-level heterogeneity in the rock and uses a realistic distribution of multiphase fluids in the pores. Unlike the relationships developed in the past, the proposed fluid morphology based method shows that the effective thermal conductivity bears a bilinear relation with fluid saturation, a trend observed in soil experiments. Explicit incorporation of pore-scale fluid morphology also shows a higher sensitivity of the effective thermal conductivity to intermediate multiphase saturations compared to an equivalent-medium representation of multiphase fluids in the pore space.