A New Inverse Modeling Approach for Hydraulic Conductivity Estimation Based on Gaussian Mixtures

Abstract This study proposes a new inverse algorithm to estimate the hydraulic conductivity (K) distribution based on a Gaussian Mixture Model that significantly reduces the number of parameters to be estimated during the inversion process. Moreover, a new objective function that increases the sensitivity of parameters using the spatial derivatives of hydraulic heads is introduced, […]